  Realistic reconstruction of 3D clothing from an image has wide applications,
such as avatar creation and virtual try-on. This paper presents a novel
framework that reconstructs the texture map for 3D garments from a single image
with pose. Assuming that 3D garments are modeled by stitching 2D garment sewing
patterns, our specific goal is to generate a texture image for the sewing
patterns. A key component of our framework, the Texture Unwarper, infers the
original texture image from the input clothing image, which exhibits warping
and occlusion of texture due to the user's body shape and pose. The Texture
Unwarper effectively transforms between the input and output images by mapping
the latent spaces of the two images. By inferring the unwarped original texture
of the input garment, our method helps reconstruct 3D garment models that can
show high-quality texture images realistically deformed for new poses. We
validate the effectiveness of our approach through a comparison with other
methods and ablation studies.
