| title | HairDeck: Animation-Ready Stylized Hair Cards from a Single Image |
|---|---|
| authors | Yuze He, Yixiang Wei, Wang Zhao, Chuhao Chen, Yanning Zhou, Yong-Jin Liu |
| date | 2026-10-29 |
| venue | arXiv (preprint, not peer reviewed) |
| id | arXiv:2610.40599 |
| affiliation | Tsinghua University |
| upvotes | 23 (Hugging Face Daily Papers, 2026-11-01) |
| links | abs pdf hf code |
| abstract | The hair of stylized characters in games and avatars is built from hair cards: artist-placed ribbons whose geometry is the visible hair, animated by spring bones. Existing image-based methods produce realistic hair or a single fused mesh, while CHARM, the only generator of stylized hair cards, decodes a hairstyle autoregressively as a long sequence of control points. Observing that a card hairstyle is an unordered set of artist-defined primitives, we propose HairDeck, which generates it as one: each card is a single token, and a set diffusion transformer denoises all cards together. From a single image, HairDeck generates the cards and the spring-bone chains that drive them, yielding an animatable asset that exports to ready-to-use downstream formats. On CHARM's own test set, it lowers Chamfer distance by 44% and card-orientation error by more than half while running 33 times faster, and from single images it outperforms CHARM, image-to-3D pipelines and strand-based methods. Project page: https://hyzcluster.github.io/HairDeck |
cite
@misc{he2026hairdeck,
title={HairDeck: Animation-Ready Stylized Hair Cards from a Single Image},
author={Yuze He and Yixiang Wei and Wang Zhao and Chuhao Chen and Yanning Zhou and Yong-Jin Liu},
year={2026},
eprint={2610.40599},
archivePrefix={arXiv},
url={https://arxiv.org/abs/2610.40599}
}