Garment Recovery with Shape and Deformation Priors

Ren Li, Corentin Dumery, Benoît Guillard, Pascal Fua; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024, pp. 1586-1595

While modeling people wearing tight-fitting clothing has made great strides in recent years loose-fitting clothing remains a challenge. We propose a method that delivers realistic garment models from real-world images regardless of garment shape or deformation. To this end we introduce a fitting approach that utilizes shape and deformation priors learned from synthetic data to accurately capture garment shapes and deformations including large ones. Not only does our approach recover the garment geometry accurately it also yields models that can be directly used by downstream applications such as animation and simulation.