从单目视频重建可动穿衣人像，分离身体与衣物分别处理。
MonoCloth: Reconstruction and Animation of Cloth-Decoupled Human Avatars from Monocular Videos
- 将人体分解为躯干、脸、手、衣物四部分，分治不同复杂度
- 衣物模块利用时序运动与几何约束模拟真实褶皱变化
- 支持换装等拓展应用，适合虚拟试衣场景
从单目视频重建逼真3D人像极具挑战，因几何信息有限且形变复杂。本文提出MonoCloth方法，通过部件分解策略将人像分为躯干、面部、双手和衣物四部分，针对不同组件的重建难度差异进行差异化处理。对脸部和双手重点恢复精细几何结构；对衣物则设计专用布料模拟模块，利用时序运动线索与几何约束捕捉服装动态形变。实验表明，相比现有方法，MonoCloth在视觉重建质量和动画真实感上均有提升。此外，其部件化设计还支持衣物迁移等附加任务，体现方法的通用性与实用价值。
原文摘要 · Abstract (English)
Reconstructing realistic 3D human avatars from monocular videos is a challenging task due to the limited geometric information and complex non-rigid motion involved. We present MonoCloth, a new method for reconstructing and animating clothed human avatars from monocular videos. To overcome the limitations of monocular input, we introduce a part-based decomposition strategy that separates the avatar into body, face, hands, and clothing. This design reflects the varying levels of reconstruction difficulty and deformation complexity across these components. Specifically, we focus on detailed geometry recovery for the face and hands. For clothing, we propose a dedicated cloth simulation module that captures garment deformation using temporal motion cues and geometric constraints. Experimental results demonstrate that MonoCloth improves both visual reconstruction quality and animation realism compared to existing methods. Furthermore, thanks to its part-based design, MonoCloth also supports additional tasks such as clothing transfer, underscoring its versatility and practical utility.
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