用物理感知方法实现高精度服装网格对齐，提升虚拟试衣效果
PhyDeformer: High-Quality Non-Rigid Garment Registration with Physics-Awareness
- 分两阶段：先粗对齐再精细优化，考虑比例缩放与版型差异
- 在合成与真实服装数据上均显著优于现有方法，对齐精度更高
- 适合虚拟试衣、数字时装设计等需要高保真服装建模的场景
我们提出PhyDeformer，一种用于高质量非刚性服装网格配准的新方法。该方法分为两个阶段：第一阶段进行服装分级，实现网格模板与目标网格之间的粗略3D对齐，考虑比例缩放和合身度（如长度、尺寸）；第二阶段通过耦合雅可比变形框架的优化，对已分级的网格进行精细化调整，以匹配目标3D形状的细节。在合成与真实服装数据上的定量与定性评估均验证了该方法的有效性。
原文摘要 · Abstract (English)
We present PhyDeformer, a new deformation method for high-quality garment mesh registration. It operates in two phases: In the first phase, a garment grading is performed to achieve a coarse 3D alignment between the mesh template and the target mesh, accounting for proportional scaling and fit (e.g. length, size). Then, the graded mesh is refined to align with the fine-grained details of the 3D target through an optimization coupled with the Jacobian-based deformation framework. Both quantitative and qualitative evaluations on synthetic and real garments highlight the effectiveness of our method.
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