游戏角色头发，现在一张图就能直接动起来
游戏和虚拟形象里的头发，从来不是一根根毛，而是美术师手工摆的「卡片」——几片带形状的薄片，再挂上弹簧骨骼，风一吹就晃。过去想从一张图生成这种头发，要么生成一团没法动的实心模型，要么像念课文一样一个点一个点地挤出来，慢且容易歪。这篇把整个发型当成一组「卡片」一次性生成：每张卡片是一个独立单元，一个扩散模型同时把所有卡片和驱动它们的骨骼链一起算出来，导出的就是能直接进引擎用的动画资产。在同类方法自己的测试集上，误差降了四成多，朝向错误减半，速度快了 33 倍。它不是你明天就能用的工具，但这是「从一张图到可动画游戏资产」这条路上，第一次把头发当成美术师手里的卡片来生成，而不是当成几何体来重建。
📄 原文摘要(英文)
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