基于模式坐标扩散映射的时空服装重建
Spatio-Temporal Garment Reconstruction Using Diffusion Mapping via Pattern Coordinates
AI总结：
本文提出了一种基于模式坐标扩散映射的时空服装重建方法，结合隐式缝合模式与生成扩散模型，实现高保真3D服装重建，适用于虚拟试穿和动画等领域。
摘要：
从单目图像和视频中重建3D穿衣人类是一个基础问题，应用于虚拟试穿、姿态创建和混合现实。尽管在人体恢复方面取得了显著进展，但准确重建服装几何，特别是松散衣物，仍然是一个开放性挑战。我们提出了一种统一框架，用于从单张图像和视频序列中进行高保真的3D服装重建。我们的方法结合了隐式缝合模式（ISP）和生成扩散模型，以学习2D UV空间中的表达性服装形状先验。利用这些先验，我们引入了一个映射模型，建立图像像素、UV模式坐标和3D几何之间的对应关系，从而从单张图像中实现精确且详细的服装重建。我们进一步将此公式扩展到动态重建，通过引入时空扩散方案和测试时指导，以强制长时间的时序一致性。我们还开发了基于解析投影的约束，以在可见区域保持图像对齐的几何结构，同时在时间上保持遮挡区域的一致性。虽然仅在合成模拟的衣物数据上训练，但我们的方法在真实世界图像中表现良好，并在紧身和松散衣物上都优于现有方法。重建的服装保留了精细的几何细节，同时表现出逼真的动态运动，支持后续应用如纹理编辑、服装重定向和动画。
英文摘要：
Reconstructing 3D clothed humans from monocular images and videos is a fundamental problem with applications in virtual try-on, avatar creation, and mixed reality. Despite significant progress in human body recovery, accurately reconstructing garment geometry, particularly for loose-fitting clothing, remains an open challenge. We propose a unified framework for high-fidelity 3D garment reconstruction from both single images and video sequences. Our approach combines Implicit Sewing Patterns (ISP) with a generative diffusion model to learn expressive garment shape priors in 2D UV space. Leveraging these priors, we introduce a mapping model that establishes correspondences between image pixels, UV pattern coordinates, and 3D geometry, enabling accurate and detailed garment reconstruction from single images. We further extend this formulation to dynamic reconstruction by introducing a spatio-temporal diffusion scheme with test-time guidance to enforce long-range temporal consistency. We also develop analytic projection-based constraints that preserve image-aligned geometry in visible regions while enforcing coherent completion in occluded areas over time. Although trained exclusively on synthetically simulated cloth data, our method generalizes well to real-world imagery and consistently outperforms existing approaches on both tight- and loose-fitting garments. The reconstructed garments preserve fine geometric detail while exhibiting realistic dynamic motion, supporting downstream applications such as texture editing, garment retargeting, and animation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
