CHARM：基于控制点的三维动漫发型自回归建模

CHARM: Control-point-based 3D Anime Hairstyle Auto-Regressive Modeling

September 25, 2025

作者: Yuze He, Yanning Zhou, Wang Zhao, Jingwen Ye, Yushi Bai, Kaiwen Xiao, Yong-Jin Liu, Zhongqian Sun, Wei Yang

cs.AI

摘要

我们提出了CHARM，一种新颖的参数化表示与生成框架，专为动漫发型建模而设计。传统发型建模方法多聚焦于采用基于发丝或体素的表示来追求真实感，而动漫发型则展现出高度风格化、分段式的几何特征，这对现有技术构成了挑战。现有工作往往依赖于密集网格建模或手工绘制的样条曲线，导致编辑效率低下且难以适应规模化学习。CHARM引入了一种紧凑、可逆的基于控制点的参数化方法，其中每个发片由一系列控制点表示，每个点仅用五个几何参数编码。这一高效且精确的表示方式既支持艺术家友好型设计，也适用于基于学习的生成。基于此表示，CHARM构建了一个自回归生成框架，能够从输入图像或点云中有效生成动漫发型。通过将动漫发型解读为一种序列化的“发语”，我们的自回归Transformer模型能够捕捉局部几何与全局发型拓扑，从而实现高保真度的动漫发型创作。为了促进动漫发型生成的训练与评估，我们构建了AnimeHair，一个包含37,000个高质量动漫发型的大规模数据集，其中每个发片均被分离并包含处理后的网格数据。大量实验证明，CHARM在重建精度与生成质量上均达到了业界领先水平，为动漫发型建模提供了一个表达力强且可扩展的解决方案。项目页面：https://hyzcluster.github.io/charm/

English

We present CHARM, a novel parametric representation and generative framework for anime hairstyle modeling. While traditional hair modeling methods focus on realistic hair using strand-based or volumetric representations, anime hairstyle exhibits highly stylized, piecewise-structured geometry that challenges existing techniques. Existing works often rely on dense mesh modeling or hand-crafted spline curves, making them inefficient for editing and unsuitable for scalable learning. CHARM introduces a compact, invertible control-point-based parameterization, where a sequence of control points represents each hair card, and each point is encoded with only five geometric parameters. This efficient and accurate representation supports both artist-friendly design and learning-based generation. Built upon this representation, CHARM introduces an autoregressive generative framework that effectively generates anime hairstyles from input images or point clouds. By interpreting anime hairstyles as a sequential "hair language", our autoregressive transformer captures both local geometry and global hairstyle topology, resulting in high-fidelity anime hairstyle creation. To facilitate both training and evaluation of anime hairstyle generation, we construct AnimeHair, a large-scale dataset of 37K high-quality anime hairstyles with separated hair cards and processed mesh data. Extensive experiments demonstrate state-of-the-art performance of CHARM in both reconstruction accuracy and generation quality, offering an expressive and scalable solution for anime hairstyle modeling. Project page: https://hyzcluster.github.io/charm/