CHARM：基於控制點的三維動漫髮型自回歸建模

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

我們提出了CHARM，一種新穎的參數化表示與生成框架，專注於動漫髮型建模。傳統的髮型建模方法主要基於髮絲或體積表示來追求真實感，而動漫髮型則展現出高度風格化、分段結構的幾何特徵，這對現有技術提出了挑戰。現有工作往往依賴於密集的網格建模或手工製作的樣條曲線，使得編輯效率低下且不適合可擴展的學習。CHARM引入了一種緊湊、可逆的基於控制點的參數化方法，其中一系列控制點代表每一片髮片，每個點僅用五個幾何參數編碼。這種高效且精確的表示既支持藝術家友好的設計，也支持基於學習的生成。基於此表示，CHARM提出了一種自迴歸生成框架，能有效地從輸入圖像或點雲生成動漫髮型。通過將動漫髮型解讀為一種序列化的“髮型語言”，我們的自迴歸變壓器模型捕捉了局部幾何與全局髮型拓撲，從而實現了高保真度的動漫髮型創作。為了促進動漫髮型生成的訓練與評估，我們構建了AnimeHair，一個包含37K高質量動漫髮型的大規模數據集，其中包含分離的髮片與處理後的網格數據。大量實驗證明了CHARM在重建精度與生成質量上的領先性能，為動漫髮型建模提供了一種表達力強且可擴展的解決方案。項目頁面：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/