Super-Resolution Cloth Animation with Spatial and Temporal Coherence

Author:

Yu Jiawang12ORCID,Wang Zhendong1ORCID

Affiliation:

1. Style3D Research, Hangzhou, China

2. Zhejiang University, Hangzhou, China

Abstract

Creating super-resolution cloth animations, which refine coarse cloth meshes with fine wrinkle details, faces challenges in preserving spatial consistency and temporal coherence across frames. In this paper, we introduce a general framework to address these issues, leveraging two core modules. The first module interleaves a simulator and a corrector. The simulator handles cloth dynamics, while the corrector rectifies differences in low-frequency features across various resolutions. This interleaving ensures prompt correction of spatial errors from the coarse simulation, effectively preventing their temporal propagation. The second module performs mesh-based super-resolution for detailed wrinkle enhancements. We decompose garment meshes into overlapping patches for adaptability to various styles and geometric continuity. Our method achieves an 8× improvement in resolution for cloth animations. We showcase the effectiveness of our method through diverse animation examples, including simple cloth pieces and intricate garments.

Funder

Key R&D Program of Zhejiang

Publisher

Association for Computing Machinery (ACM)

Reference66 articles.

1. Ferran Alet, Adarsh Keshav Jeewajee, Maria Bauza Villalonga, Alberto Rodriguez, Tomas Lozano-Perez, and Leslie Kaelbling. 2019. Graph element networks: adaptive, structured computation and memory. In International Conference on Machine Learning. PMLR, 212--222.

2. Saeed Anwar, Salman Khan, and Nick Barnes. 2020. A Deep Journey into Super-resolution: A Survey. ACM Comput. Surv. 53, 3, Article 60 (may 2020), 34 pages.

3. Large steps in cloth simulation

4. Neural Cloth Simulation

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