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

Towards Loose-Fitting Garment Animation via Generative Model of Deformation Decomposition (2312.14619v1)

Published 22 Dec 2023 in cs.CV

Abstract: Existing data-driven methods for garment animation, usually driven by linear skinning, although effective on tight garments, do not handle loose-fitting garments with complex deformations well. To address these limitations, we develop a garment generative model based on deformation decomposition to efficiently simulate loose garment deformation without directly using linear skinning. Specifically, we learn a garment generative space with the proposed generative model, where we decouple the latent representation into unposed deformed garments and dynamic offsets during the decoding stage. With explicit garment deformations decomposition, our generative model is able to generate complex pose-driven deformations on canonical garment shapes. Furthermore, we learn to transfer the body motions and previous state of the garment to the latent space to regenerate dynamic results. In addition, we introduce a detail enhancement module in an adversarial training setup to learn high-frequency wrinkles. We demonstrate our method outperforms state-of-the-art data-driven alternatives through extensive experiments and show qualitative and quantitative analysis of results.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (39)
  1. Large steps in cloth simulation. In Proceedings of the 25th annual conference on Computer graphics and interactive techniques, pages 43–54, 1998.
  2. Cloth3d: clothed 3d humans. In Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XX 16, pages 344–359. Springer, 2020.
  3. Pbns: physically based neural simulation for unsupervised garment pose space deformation. ACM Transactions on Graphics (TOG), 40(6):1–14, 2021a.
  4. Deepsd: Automatic deep skinning and pose space deformation for 3d garment animation. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 5471–5480, 2021b.
  5. Neural cloth simulation. ACM Transactions on Graphics (TOG), 41(6):1–14, 2022.
  6. Estimating cloth simulation parameters from video. 2003.
  7. Neural deformation graphs for globally-consistent non-rigid reconstruction. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 1450–1459, 2021.
  8. Robust treatment of collisions, contact and friction for cloth animation. In Proceedings of the 29th annual conference on Computer graphics and interactive techniques, pages 594–603, 2002.
  9. Stable but responsive cloth. In ACM SIGGRAPH 2005 Courses, pages 1–es. 2005.
  10. Learning to forget: Continual prediction with lstm. Neural computation, 12(10):2451–2471, 2000.
  11. Garnet: A two-stream network for fast and accurate 3d cloth draping. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 8739–8748, 2019.
  12. Smooth skinning decomposition with rigid bones. ACM Transactions on Graphics (TOG), 31(6):1–10, 2012.
  13. Smpl: A skinned multi-person linear model. ACM transactions on graphics (TOG), 34(6):1–16, 2015.
  14. Learning to dress 3d people in generative clothing. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 6469–6478, 2020.
  15. Scale: Modeling clothed humans with a surface codec of articulated local elements. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 16082–16093, 2021a.
  16. The power of points for modeling humans in clothing. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 10974–10984, 2021b.
  17. Least squares generative adversarial networks. In Proceedings of the IEEE international conference on computer vision, pages 2794–2802, 2017.
  18. Data-driven estimation of cloth simulation models. In Computer Graphics Forum, pages 519–528. Wiley Online Library, 2012.
  19. Wrinkle meshes. In Symposium on Computer Animation, pages 85–91. Madrid, Spain, 2010.
  20. Physically based deformable models in computer graphics. In Computer graphics forum, pages 809–836. Wiley Online Library, 2006.
  21. Predicting loose-fitting garment deformations using bone-driven motion networks. In ACM SIGGRAPH 2022 Conference Proceedings, pages 1–10, 2022.
  22. Pytorch: An imperative style, high-performance deep learning library. Advances in neural information processing systems, 32, 2019.
  23. Tailornet: Predicting clothing in 3d as a function of human pose, shape and garment style. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 7365–7375, 2020.
  24. Learning mesh-based simulation with graph networks. arXiv preprint arXiv:2010.03409, 2020.
  25. Xavier Provot. Collision and self-collision handling in cloth model dedicated to design garments. In Computer Animation and Simulation’97: Proceedings of the Eurographics Workshop in Budapest, Hungary, September 2–3, 1997, pages 177–189. Springer, 1997.
  26. Animation wrinkling: augmenting coarse cloth simulations with realistic-looking wrinkles. ACM Transactions on Graphics (ToG), 29(6):1–8, 2010.
  27. Scanimate: Weakly supervised learning of skinned clothed avatar networks. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 2886–2897, 2021.
  28. Learning-Based Animation of Clothing for Virtual Try-On. Computer Graphics Forum (Proc. Eurographics), 2019.
  29. Self-supervised collision handling via generative 3d garment models for virtual try-on. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 11763–11773, 2021.
  30. Snug: Self-supervised neural dynamic garments. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 8140–8150, 2022.
  31. Deepcloth: Neural garment representation for shape and style editing. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(2):1581–1593, 2022.
  32. Asynchronous cloth simulation. In Computer Graphics International, page 2. Citeseer, 2008.
  33. Neural-gif: Neural generalized implicit functions for animating people in clothing. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 11708–11718, 2021.
  34. A perception correlated comparison method for dynamic meshes. IEEE transactions on visualization and computer graphics, 17(2):220–230, 2010.
  35. Leverage the average: an analysis of kl regularization in reinforcement learning. Advances in Neural Information Processing Systems, 33:12163–12174, 2020.
  36. Learning an intrinsic garment space for interactive authoring of garment animation. ACM Transactions on Graphics (TOG), 38(6):1–12, 2019a.
  37. Dynamic graph cnn for learning on point clouds. Acm Transactions On Graphics (tog), 38(5):1–12, 2019b.
  38. Dynamic neural garments. ACM Transactions on Graphics (TOG), 40(6):1–15, 2021.
  39. Motion guided deep dynamic 3d garments. ACM Transactions on Graphics (TOG), 41(6):1–12, 2022.

Summary

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

Ai Sparkles Streamline Icon: https://streamlinehq.com Summarize Now