  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.
