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Poster

Garment Recovery with Shape and Deformation Priors

Ren Li · Corentin Dumery · BenoĆ®t Guillard · Pascal Fua

Arch 4A-E Poster #138
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[ Poster
Wed 19 Jun 10:30 a.m. PDT — noon PDT

Abstract:

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.

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