Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
133 tokens/sec
GPT-4o
12 tokens/sec
Gemini 2.5 Pro Pro
42 tokens/sec
o3 Pro
5 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Isotropic Gaussian Splatting for Real-Time Radiance Field Rendering (2403.14244v1)

Published 21 Mar 2024 in cs.CV, cs.AI, cs.LG, and eess.IV

Abstract: The 3D Gaussian splatting method has drawn a lot of attention, thanks to its high performance in training and high quality of the rendered image. However, it uses anisotropic Gaussian kernels to represent the scene. Although such anisotropic kernels have advantages in representing the geometry, they lead to difficulties in terms of computation, such as splitting or merging two kernels. In this paper, we propose to use isotropic Gaussian kernels to avoid such difficulties in the computation, leading to a higher performance method. The experiments confirm that the proposed method is about {\bf 100X} faster without losing the geometry representation accuracy. The proposed method can be applied in a large range applications where the radiance field is needed, such as 3D reconstruction, view synthesis, and dynamic object modeling.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (22)
  1. “3d gaussian splatting for real-time radiance field rendering,” ACM Trans. Graph., vol. 42, no. 4, jul 2023.
  2. “Mip-splatting: Alias-free 3d gaussian splatting,” arXiv:2311.16493, 2023.
  3. “Sugar: Surface-aligned gaussian splatting for efficient 3d mesh reconstruction and high-quality mesh rendering,” arXiv preprint arXiv:2311.12775, 2023.
  4. “Removing scattered light in biomedical images,” in 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), 2023, pp. 1–5.
  5. “Curvature-driven multi-stream network for feature-preserving mesh denoising,” Computer Graphics Forum, vol. n/a, no. n/a, pp. e14993.
  6. “3d hand bones and tissue estimation from a single 2d x-ray image via a two-stream deep neural network,” in 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), 2023, pp. 1–5.
  7. “A self-organizing lagrangian particle method for adaptive-resolution advection–diffusion simulations,” Journal of Computational Physics, vol. 231, no. 9, pp. 3623–3646, 2012.
  8. “Mrag-i2d: Multi-resolution adapted grids for remeshed vortex methods on multicore architectures,” Journal of Computational Physics, vol. 288, pp. 1–18, 2015.
  9. “A local curvature based adaptive particle level set method,” Journal of Scientific Computing, vol. 91, no. 1, pp. 3, 2022.
  10. “Differentiable surface splatting for point-based geometry processing,” ACM Trans. Graph., vol. 38, no. 6, nov 2019.
  11. “Point-nerf: Point-based neural radiance fields,” New Orleans, LA, USA, 2022, pp. 5428–5438, IEEE.
  12. “Adaptive particle representation of fluorescence microscopy images,” Nature Communications, vol. 9, no. 1, pp. 5160, 2018.
  13. Y. Gong and I.F. Sbalzarini, “A natural-scene gradient distribution prior and its application in light-microscopy image processing,” Selected Topics in Signal Processing, IEEE Journal of, vol. 10, no. 1, pp. 99–114, Feb 2016.
  14. “Regression-based camera pose estimation through multi-level local features and global features,” Sensors, vol. 23, no. 8, 2023.
  15. “Single image interpolation exploiting semi-local similarity,” Brighton, UK, 2019, pp. 1722–1726, IEEE.
  16. “Curvature filters efficiently reduce certain variational energies,” IEEE Transactions on Image Processing, vol. 26, no. 4, pp. 1786–1798, April 2017.
  17. “Fast and high-quality blind multi-spectral image pansharpening,” IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1–17, 2022.
  18. “Feature preserving 3d mesh denoising with a dense local graph neural network,” vol. 233, pp. 103710, 2023.
  19. “Blind multi-spectral image pan-sharpening,” in ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, pp. 1429–1433.
  20. “Weighted mean curvature,” Signal Processing, vol. 164, pp. 329 – 339, 2019.
  21. “Side window filtering,” in Proc. IEEE/CVF Conf. Computer Vision and Pattern Recognition (CVPR), 2019, pp. 8750–8758.
  22. “Gc-net: An unsupervised network for gaussian curvature optimization on images,” Journal of Signal Processing Systems, vol. 95, no. 1, pp. 77–88, 2023.
Citations (3)

Summary

We haven't generated a summary for this paper yet.