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HairDeck:从单张图像生成动画就绪的卡通发型卡牌

HairDeck: Animation-Ready Stylized Hair Cards from a Single Image

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HairDeck 使用扩散 Transformer 从单张图像生成卡通发型卡牌和弹簧骨动画,准确性和速度优于现有方法。它将发型视为艺术家定义的原始集,通过扩散 Transformer 一起去噪生成每个卡牌为单个 token 的发型。

正文

Published on Oct 29

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Abstract

HairDeck generates stylized hair cards and spring-bone animations as unordered token sets using a diffusion transformer, improving accuracy and speed over prior methods.

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

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