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Efficient EndoNeRF Reconstruction and Its Application for Data-driven Surgical Simulation (2404.15339v1)
Published 10 Apr 2024 in eess.IV
Abstract: The healthcare industry has a growing need for realistic modeling and efficient simulation of surgical scenes. With effective models of deformable surgical scenes, clinicians are able to conduct surgical planning and surgery training on scenarios close to real-world cases. However, a significant challenge in achieving such a goal is the scarcity of high-quality soft tissue models with accurate shapes and textures. To address this gap, we present a data-driven framework that leverages emerging neural radiance field technology to enable high-quality surgical reconstruction and explore its application for surgical simulations. We first focus on developing a fast NeRF-based surgical scene 3D reconstruction approach that achieves state-of-the-art performance. This method can significantly outperform traditional 3D reconstruction methods, which have failed to capture large deformations and produce fine-grained shapes and textures. We then propose an automated creation pipeline of interactive surgical simulation environments through a closed mesh extraction algorithm. Our experiments have validated the superior performance and efficiency of our proposed approach in surgical scene 3D reconstruction. We further utilize our reconstructed soft tissues to conduct FEM and MPM simulations, showcasing the practical application of our method in data-driven surgical simulations.
- Chen, W., Liao, X., Sun, Y., Wang, Q.: Improved orb-slam based 3d dense reconstruction for monocular endoscopic image. In: ICVRV, pp. 101–106 (2020) Recasens et al. [2021] Recasens, D., Lamarca, J., Fácil, J.M., Montiel, J., Civera, J.: Endo-depth-and-motion: Reconstruction and tracking in endoscopic videos using depth networks and photometric constraints. IEEE Robotics and Automation Letters 6(4), 7225–7232 (2021) Wei et al. [2021] Wei, G., Yang, H., Shi, W., Jiang, Z., Chen, T., Wang, Y.: Laparoscopic scene reconstruction based on multiscale feature patch tracking method. In: EIECS, pp. 588–592 (2021). IEEE Wei et al. [2022] Wei, R., Li, B., Mo, H., Lu, B., Long, Y., Yang, B., Dou, Q., Liu, Y., Sun, D.: Stereo dense scene reconstruction and accurate localization for learning-based navigation of laparoscope in minimally invasive surgery. IEEE Transactions on Biomedical Engineering 70(2), 488–500 (2022) Long et al. [2021] Long, Y., Li, Z., Yee, C.H., Ng, C.F., Taylor, R.H., Unberath, M., Dou, Q.: E-dssr: efficient dynamic surgical scene reconstruction with transformer-based stereoscopic depth perception. In: MICCAI, pp. 415–425 (2021) Wang et al. [2022] Wang, Y., Long, Y., Fan, S.H., Dou, Q.: Neural rendering for stereo 3d reconstruction of deformable tissues in robotic surgery. MICCAI (2022) Mildenhall et al. [2020] Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: ECCV, pp. 405–421 (2020) Müller et al. [2007] Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Recasens, D., Lamarca, J., Fácil, J.M., Montiel, J., Civera, J.: Endo-depth-and-motion: Reconstruction and tracking in endoscopic videos using depth networks and photometric constraints. IEEE Robotics and Automation Letters 6(4), 7225–7232 (2021) Wei et al. [2021] Wei, G., Yang, H., Shi, W., Jiang, Z., Chen, T., Wang, Y.: Laparoscopic scene reconstruction based on multiscale feature patch tracking method. In: EIECS, pp. 588–592 (2021). IEEE Wei et al. [2022] Wei, R., Li, B., Mo, H., Lu, B., Long, Y., Yang, B., Dou, Q., Liu, Y., Sun, D.: Stereo dense scene reconstruction and accurate localization for learning-based navigation of laparoscope in minimally invasive surgery. IEEE Transactions on Biomedical Engineering 70(2), 488–500 (2022) Long et al. [2021] Long, Y., Li, Z., Yee, C.H., Ng, C.F., Taylor, R.H., Unberath, M., Dou, Q.: E-dssr: efficient dynamic surgical scene reconstruction with transformer-based stereoscopic depth perception. In: MICCAI, pp. 415–425 (2021) Wang et al. [2022] Wang, Y., Long, Y., Fan, S.H., Dou, Q.: Neural rendering for stereo 3d reconstruction of deformable tissues in robotic surgery. MICCAI (2022) Mildenhall et al. [2020] Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: ECCV, pp. 405–421 (2020) Müller et al. [2007] Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wei, G., Yang, H., Shi, W., Jiang, Z., Chen, T., Wang, Y.: Laparoscopic scene reconstruction based on multiscale feature patch tracking method. In: EIECS, pp. 588–592 (2021). IEEE Wei et al. [2022] Wei, R., Li, B., Mo, H., Lu, B., Long, Y., Yang, B., Dou, Q., Liu, Y., Sun, D.: Stereo dense scene reconstruction and accurate localization for learning-based navigation of laparoscope in minimally invasive surgery. IEEE Transactions on Biomedical Engineering 70(2), 488–500 (2022) Long et al. [2021] Long, Y., Li, Z., Yee, C.H., Ng, C.F., Taylor, R.H., Unberath, M., Dou, Q.: E-dssr: efficient dynamic surgical scene reconstruction with transformer-based stereoscopic depth perception. In: MICCAI, pp. 415–425 (2021) Wang et al. [2022] Wang, Y., Long, Y., Fan, S.H., Dou, Q.: Neural rendering for stereo 3d reconstruction of deformable tissues in robotic surgery. MICCAI (2022) Mildenhall et al. [2020] Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: ECCV, pp. 405–421 (2020) Müller et al. [2007] Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wei, R., Li, B., Mo, H., Lu, B., Long, Y., Yang, B., Dou, Q., Liu, Y., Sun, D.: Stereo dense scene reconstruction and accurate localization for learning-based navigation of laparoscope in minimally invasive surgery. IEEE Transactions on Biomedical Engineering 70(2), 488–500 (2022) Long et al. [2021] Long, Y., Li, Z., Yee, C.H., Ng, C.F., Taylor, R.H., Unberath, M., Dou, Q.: E-dssr: efficient dynamic surgical scene reconstruction with transformer-based stereoscopic depth perception. In: MICCAI, pp. 415–425 (2021) Wang et al. [2022] Wang, Y., Long, Y., Fan, S.H., Dou, Q.: Neural rendering for stereo 3d reconstruction of deformable tissues in robotic surgery. MICCAI (2022) Mildenhall et al. [2020] Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: ECCV, pp. 405–421 (2020) Müller et al. [2007] Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, Z., Yee, C.H., Ng, C.F., Taylor, R.H., Unberath, M., Dou, Q.: E-dssr: efficient dynamic surgical scene reconstruction with transformer-based stereoscopic depth perception. In: MICCAI, pp. 415–425 (2021) Wang et al. [2022] Wang, Y., Long, Y., Fan, S.H., Dou, Q.: Neural rendering for stereo 3d reconstruction of deformable tissues in robotic surgery. MICCAI (2022) Mildenhall et al. [2020] Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: ECCV, pp. 405–421 (2020) Müller et al. [2007] Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wang, Y., Long, Y., Fan, S.H., Dou, Q.: Neural rendering for stereo 3d reconstruction of deformable tissues in robotic surgery. MICCAI (2022) Mildenhall et al. [2020] Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: ECCV, pp. 405–421 (2020) Müller et al. [2007] Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: ECCV, pp. 405–421 (2020) Müller et al. [2007] Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. 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ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. 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ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. 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[2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. 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[2022] Wei, R., Li, B., Mo, H., Lu, B., Long, Y., Yang, B., Dou, Q., Liu, Y., Sun, D.: Stereo dense scene reconstruction and accurate localization for learning-based navigation of laparoscope in minimally invasive surgery. IEEE Transactions on Biomedical Engineering 70(2), 488–500 (2022) Long et al. [2021] Long, Y., Li, Z., Yee, C.H., Ng, C.F., Taylor, R.H., Unberath, M., Dou, Q.: E-dssr: efficient dynamic surgical scene reconstruction with transformer-based stereoscopic depth perception. In: MICCAI, pp. 415–425 (2021) Wang et al. [2022] Wang, Y., Long, Y., Fan, S.H., Dou, Q.: Neural rendering for stereo 3d reconstruction of deformable tissues in robotic surgery. MICCAI (2022) Mildenhall et al. [2020] Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: ECCV, pp. 405–421 (2020) Müller et al. [2007] Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. 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In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wei, R., Li, B., Mo, H., Lu, B., Long, Y., Yang, B., Dou, Q., Liu, Y., Sun, D.: Stereo dense scene reconstruction and accurate localization for learning-based navigation of laparoscope in minimally invasive surgery. IEEE Transactions on Biomedical Engineering 70(2), 488–500 (2022) Long et al. [2021] Long, Y., Li, Z., Yee, C.H., Ng, C.F., Taylor, R.H., Unberath, M., Dou, Q.: E-dssr: efficient dynamic surgical scene reconstruction with transformer-based stereoscopic depth perception. In: MICCAI, pp. 415–425 (2021) Wang et al. [2022] Wang, Y., Long, Y., Fan, S.H., Dou, Q.: Neural rendering for stereo 3d reconstruction of deformable tissues in robotic surgery. MICCAI (2022) Mildenhall et al. [2020] Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: ECCV, pp. 405–421 (2020) Müller et al. [2007] Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. 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[2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, Z., Yee, C.H., Ng, C.F., Taylor, R.H., Unberath, M., Dou, Q.: E-dssr: efficient dynamic surgical scene reconstruction with transformer-based stereoscopic depth perception. In: MICCAI, pp. 415–425 (2021) Wang et al. [2022] Wang, Y., Long, Y., Fan, S.H., Dou, Q.: Neural rendering for stereo 3d reconstruction of deformable tissues in robotic surgery. MICCAI (2022) Mildenhall et al. [2020] Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: ECCV, pp. 405–421 (2020) Müller et al. [2007] Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wang, Y., Long, Y., Fan, S.H., Dou, Q.: Neural rendering for stereo 3d reconstruction of deformable tissues in robotic surgery. MICCAI (2022) Mildenhall et al. [2020] Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: ECCV, pp. 405–421 (2020) Müller et al. [2007] Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: ECCV, pp. 405–421 (2020) Müller et al. [2007] Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. 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ACM Transactions on Graphics (TOG) 39(4) (2020) Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. 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[2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. 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ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. 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[2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wei, R., Li, B., Mo, H., Lu, B., Long, Y., Yang, B., Dou, Q., Liu, Y., Sun, D.: Stereo dense scene reconstruction and accurate localization for learning-based navigation of laparoscope in minimally invasive surgery. IEEE Transactions on Biomedical Engineering 70(2), 488–500 (2022) Long et al. [2021] Long, Y., Li, Z., Yee, C.H., Ng, C.F., Taylor, R.H., Unberath, M., Dou, Q.: E-dssr: efficient dynamic surgical scene reconstruction with transformer-based stereoscopic depth perception. In: MICCAI, pp. 415–425 (2021) Wang et al. [2022] Wang, Y., Long, Y., Fan, S.H., Dou, Q.: Neural rendering for stereo 3d reconstruction of deformable tissues in robotic surgery. MICCAI (2022) Mildenhall et al. [2020] Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: ECCV, pp. 405–421 (2020) Müller et al. [2007] Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, Z., Yee, C.H., Ng, C.F., Taylor, R.H., Unberath, M., Dou, Q.: E-dssr: efficient dynamic surgical scene reconstruction with transformer-based stereoscopic depth perception. In: MICCAI, pp. 415–425 (2021) Wang et al. [2022] Wang, Y., Long, Y., Fan, S.H., Dou, Q.: Neural rendering for stereo 3d reconstruction of deformable tissues in robotic surgery. MICCAI (2022) Mildenhall et al. [2020] Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: ECCV, pp. 405–421 (2020) Müller et al. [2007] Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wang, Y., Long, Y., Fan, S.H., Dou, Q.: Neural rendering for stereo 3d reconstruction of deformable tissues in robotic surgery. MICCAI (2022) Mildenhall et al. [2020] Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: ECCV, pp. 405–421 (2020) Müller et al. [2007] Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: ECCV, pp. 405–421 (2020) Müller et al. [2007] Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. 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ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. 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[2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
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[2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. 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ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, Z., Yee, C.H., Ng, C.F., Taylor, R.H., Unberath, M., Dou, Q.: E-dssr: efficient dynamic surgical scene reconstruction with transformer-based stereoscopic depth perception. In: MICCAI, pp. 415–425 (2021) Wang et al. [2022] Wang, Y., Long, Y., Fan, S.H., Dou, Q.: Neural rendering for stereo 3d reconstruction of deformable tissues in robotic surgery. MICCAI (2022) Mildenhall et al. [2020] Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: ECCV, pp. 405–421 (2020) Müller et al. [2007] Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wang, Y., Long, Y., Fan, S.H., Dou, Q.: Neural rendering for stereo 3d reconstruction of deformable tissues in robotic surgery. MICCAI (2022) Mildenhall et al. [2020] Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: ECCV, pp. 405–421 (2020) Müller et al. [2007] Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: ECCV, pp. 405–421 (2020) Müller et al. [2007] Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. 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[2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. 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[1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. 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[2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: ECCV, pp. 405–421 (2020) Müller et al. [2007] Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. 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In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. 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ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. 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[2007] Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
- Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: ECCV, pp. 405–421 (2020) Müller et al. [2007] Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. 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[2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. Journal of Visual Communication and Image Representation 18(2), 109–118 (2007) Sifakis and Barbic [2012] Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sifakis, E., Barbic, J.: Fem simulation of 3d deformable solids: a practitioner’s guide to theory, discretization and model reduction. In: Acm Siggraph 2012 Courses, pp. 1–50 (2012) Qian et al. [2017] Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. 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ACM Transactions on Graphics (TOG) 39(4) (2020) Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. 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ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. 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[2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. 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In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. 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[2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. 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In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. 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ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. 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[2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. 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ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. 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[2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. 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ACM Transactions on Graphics (TOG) 39(4) (2020) Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. 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ACM Transactions on Graphics (TOG) 39(4) (2020) Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. 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[2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. 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ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. 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In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. 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In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. 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ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. 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[2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
- Qian, K., Bai, J., Yang, X., Pan, J., Zhang, J.: Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds 28(2), 1724 (2017) Qian et al. [2016] Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Qian, K., Jiang, T., Wang, M., Yang, X., Zhang, J.: Energized soft tissue dissection in surgery simulation. Computer Animation and Virtual Worlds 27(3-4), 280–289 (2016) Hu et al. [2019] Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. 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ACM Transactions on Graphics (TOG) 39(4) (2020) Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. 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[2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. 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[2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. 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[2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. 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[1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. 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[2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
- Hu, Y., Li, T.-M., Anderson, L., Ragan-Kelley, J., Durand, F.: Taichi: a language for high-performance computation on spatially sparse data structures. ACM Transactions on Graphics (TOG) 38(6), 1–16 (2019) Hu et al. [2018] Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
- Hu, Y., Fang, Y., Ge, Z., Qu, Z., Zhu, Y., Pradhana, A., Jiang, C.: A moving least squares material point method with displacement discontinuity and two-way rigid body coupling. ACM Transactions on Graphics (TOG) 37(4), 1–14 (2018) Liang et al. [2018] Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Liang, J., Makoviychuk, V., Handa, A., Chentanez, N., Macklin, M., Fox, D.: Gpu-accelerated robotic simulation for distributed reinforcement learning. In: CoRL, pp. 270–282 (2018). PMLR Müller et al. [2022] Müller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Transactions on Graphics (ToG) 41(4), 1–15 (2022) Sun et al. [2022] Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. 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In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. 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ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. 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[2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. 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[2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
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[2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. 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ACM Transactions on Graphics (TOG) 39(4) (2020) Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. 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[2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. 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ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
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In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sun, C., Sun, M., Chen, H.-T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: CVPR (2022) Fridovich-Keil et al. [2022] Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: CVPR, pp. 5501–5510 (2022) Fridovich-Keil et al. [2023] Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
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[2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. 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[2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Fridovich-Keil, S., Meanti, G., Warburg, F.R., Recht, B., Kanazawa, A.: K-planes: Explicit radiance fields in space, time, and appearance. In: CVPR, pp. 12479–12488 (2023) Pumarola et al. [2021] Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Pumarola, A., Corona, E., Pons-Moll, G., Moreno-Noguer, F.: D-nerf: Neural radiance fields for dynamic scenes. In: CVPR, pp. 10318–10327 (2021) Park et al. [2021] Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. 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[2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. 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In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. 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ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. 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ACM Transactions on Graphics (TOG) 39(4) (2020) Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. 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[2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. 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ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
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ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. 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ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. 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ACM Transactions on Graphics (TOG) 39(4) (2020) Park, K., Sinha, U., Barron, J.T., Bouaziz, S., Goldman, D.B., Seitz, S.M., Martin-Brualla, R.: Nerfies: Deformable neural radiance fields. In: ICCV, pp. 5865–5874 (2021) Chen et al. [2022] Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: Tensorial radiance fields. In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. 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In: ECCV, pp. 333–350 (2022) Cao and Johnson [2023] Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: CVPR, pp. 130–141 (2023) Xu et al. [2023] Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
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ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. 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[2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. 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[2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. 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[2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
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[2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. 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[2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
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[2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
- Xu, H., Zhang, J., Cai, J., Rezatofighi, H., Yu, F., Tao, D., Geiger, A.: Unifying flow, stereo and depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Li et al. [2021] Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Li, Z., Liu, X., Drenkow, N., Ding, A., Creighton, F.X., Taylor, R.H., Unberath, M.: Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers. In: ICCV, pp. 6197–6206 (2021) Huber [1992] Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. 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IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. 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ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
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ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Huber, P.J.: Robust estimation of a location parameter. In: Breakthroughs in Statistics: Methodology and Distribution, pp. 492–518 (1992) Wang et al. [2020] Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. 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[2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
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ACM Transactions on Graphics (TOG) 39(4) (2020) Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
- Wang, X., Qiu, Y., Slattery, S.R., Fang, Y., Li, M., Zhu, S.-C., Zhu, Y., Tang, M., Manocha, D., Jiang, C.: A massively parallel and scalable multi-gpu material point method. ACM Transactions on Graphics (TOG) 39(4), 30–1 (2020) Hu et al. [2018] Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
- Hu, Y., Zhou, Q., Gao, X., Jacobson, A., Zorin, D., Panozzo, D.: Tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 37(4), 60–1 (2018) Hu et al. [2020] Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
- Hu, Y., Schneider, T., Wang, B., Zorin, D., Panozzo, D.: Fast tetrahedral meshing in the wild. ACM Transactions on Graphics (TOG) 39(4), 117–1 (2020) Si [2015] Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
- Si, H.: Tetgen, a delaunay-based quality tetrahedral mesh generator. ACM Trans. Math. Softw. 41(2) (2015) https://doi.org/10.1145/2629697 Long et al. [2022] Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
- Long, Y., Li, C., Dou, Q.: Robotic surgery remote mentoring via ar with 3d scene streaming and hand interaction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 1–6 (2022) Long et al. [2023] Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
- Long, Y., Wei, W., Huang, T., Wang, Y., Dou, Q.: Human-in-the-loop embodied intelligence with interactive simulation environment for surgical robot learning. IEEE Robotics and Automation Letters (2023) Sulsky et al. [1995] Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
- Sulsky, D., Zhou, S.-J., Schreyer, H.L.: Application of a particle-in-cell method to solid mechanics. Computer physics communications 87(1-2), 236–252 (1995) Wolper et al. [2019] Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
- Wolper, J., Fang, Y., Li, M., Lu, J., Gao, M., Jiang, C.: Cd-mpm: continuum damage material point methods for dynamic fracture animation. ACM Transactions on Graphics (TOG) 38(4), 1–15 (2019) Wolper et al. [2020] Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020) Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)
- Wolper, J., Chen, Y., Li, M., Fang, Y., Qu, Z., Lu, J., Cheng, M., Jiang, C.: Anisompm: Animating anisotropic damage mechanics. ACM Transactions on Graphics (TOG) 39(4) (2020)