PhyDeformer: High-Quality Non-Rigid Garment Registration with Physics-Awareness
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Date
2025
Authors
Journal Title
Journal ISSN
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Publisher
The Eurographics Association
Abstract
Accurately registering 3D garment meshes to real-world image data is a fundamental yet challenging task in computer vision and graphics, with applications in virtual try-on systems, digital fashion, performance capture, and virtual content creation. This problem involves recovering detailed, non-rigid garment geometry from partial, noisy, and often ambiguous visual cues extracted from 2D or reconstructed 3D data. A key challenge lies in aligning garment templates with target shapes while preserving realistic fabric behavior and accommodating variations in body shape, garment fit, and pose. 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). In the second phase, the graded mesh is refined to capture fine-grained geometric details of the 3D target through a localized optimization process, leveraging a Jacobian-based deformation framework. Both quantitative and qualitative evaluations on synthetic and real garment data demonstrate the effectiveness and robustness of our method in achieving accurate and visually plausible registrations. The code and base meshes generated and evaluated in this paper are available at https://github.com/MLMS-CG/PhyDeformer.
Description
@inproceedings{10.2312:3dor.20251200,
booktitle = {Eurographics Workshop on 3D Object Retrieval},
editor = {Guerrero, Paul and Pratikakis, Ioannis and Veltkamp, Remco},
title = {{PhyDeformer: High-Quality Non-Rigid Garment Registration with Physics-Awareness}},
author = {Yu, Boyang and Cordier, Frederic and Seo, Hyewon},
year = {2025},
publisher = {The Eurographics Association},
ISSN = {1997-0471},
ISBN = {978-3-03868-280-6},
DOI = {10.2312/3dor.20251200}
}