PhysAvatar: Learning the Physics of Dressed 3D Avatars from Visual Observations
Abstract
[width=0.9]figure/teaserv 4.pdf Figure 1: PhysAvatar is a novel framework that captures the physics of dressed 3D avatars from visual observations, enabling a wide spectrum of applications, such as (a) animation, (b) relighting, and (c) redressing, with high-fidelity rendering results.
Cite
Text
Zheng et al. "PhysAvatar: Learning the Physics of Dressed 3D Avatars from Visual Observations." Proceedings of the European Conference on Computer Vision (ECCV), 2024. doi:10.1007/978-3-031-72913-3_15Markdown
[Zheng et al. "PhysAvatar: Learning the Physics of Dressed 3D Avatars from Visual Observations." Proceedings of the European Conference on Computer Vision (ECCV), 2024.](https://mlanthology.org/eccv/2024/zheng2024eccv-physavatar/) doi:10.1007/978-3-031-72913-3_15BibTeX
@inproceedings{zheng2024eccv-physavatar,
title = {{PhysAvatar: Learning the Physics of Dressed 3D Avatars from Visual Observations}},
author = {Zheng, Yang and Zhao, Qingqing and Yang, Guandao and Yifan, Wang and Xiang, Donglai and Dubost, Florian and Lagun, Dmitry and Beeler, Thabo and Tombari, Federico and Guibas, Leonidas and Wetzstein, Gordon},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
year = {2024},
doi = {10.1007/978-3-031-72913-3_15},
url = {https://mlanthology.org/eccv/2024/zheng2024eccv-physavatar/}
}