从单张图像无监督重建复杂发辫的3D结构。
Unsupervised 3D Braided Hair Reconstruction from a Single-View Image
- 基于辫子理论构建合成模型，捕捉发辫缠绕结构。
- 相比现有方法，重建更准确、真实且高效。
- 适合数字人发型建模与虚拟角色设计。
从单视角图像重建3D发辫发型仍具挑战，因其复杂的交织结构与拓扑关系。现有基于发丝的重建方法多针对松散发型，难以捕捉发辫的精细几何特征。本文提出一种新型无监督管道，可高效实现从单张RGB图像重建3D发辫发型。该方法借鉴辫子理论构建合成发辫模型，有效表征发辫的复杂缠绕结构。大量实验表明，本方法优于当前最优方法，在准确性、真实性和效率方面均表现更优，支持数字人中富有表现力的发型建模。
原文摘要 · Abstract (English)
Reconstructing 3D braided hairstyles from single-view images remains a challenging task due to the intricate interwoven structure and complex topologies of braids. Existing strand-based hair reconstruction methods typically focus on loose hairstyles and often struggle to capture the fine-grained geometry of braided hair. In this paper, we propose a novel unsupervised pipeline for efficiently reconstructing 3D braided hair from single-view RGB images. Leveraging a synthetic braid model inspired by braid theory, our approach effectively captures the complex intertwined structures of braids. Extensive experiments demonstrate that our method outperforms state-of-the-art approaches, providing superior accuracy, realism, and efficiency in reconstructing 3D braided hairstyles, supporting expressive hairstyle modeling in digital humans.
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