GRCVSep 25, 2025

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

arXiv:2509.21114v12 citationsh-index: 6SIGGRAPH Asia
Originality Incremental advance
AI Analysis

This work addresses the challenge of efficient and scalable anime hairstyle modeling for artists and creators, though it is incremental as it builds on existing parametric and generative methods.

The authors tackled the problem of modeling highly stylized anime hairstyles by introducing CHARM, a control-point-based parametric representation and autoregressive generative framework, which achieved state-of-the-art performance in reconstruction accuracy and generation quality on a new dataset of 37K hairstyles.

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/

Foundations

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