Cloth2Tex: A Customized Cloth Texture Generation Pipeline for 3D Virtual
  Try-On
Daiheng Gao Xu Chen Xindi Zhang Qi Wang Ke Sun Bang Zhang Liefeng Bo Qixing Huang
Fabricating and designing 3D garments has become extremely demanding with the
increasing need for synthesizing realistic dressed persons for a variety of
applications, e.g. 3D virtual try-on, digitalization of 2D clothes into 3D
apparel, and cloth animation. It thus necessitates a simple and straightforward
pipeline to obtain high-quality texture from simple input, such as 2D reference
images. Since traditional warping-based texture generation methods require a
significant number of control points to be manually selected for each type of
garment, which can be a time-consuming and tedious process. We propose a novel
method, called Cloth2Tex, which eliminates the human burden in this process.
Cloth2Tex is a self-supervised method that generates texture maps with
reasonable layout and structural consistency. Another key feature of Cloth2Tex
is that it can be used to support high-fidelity texture inpainting. This is
done by combining Cloth2Tex with a prevailing latent diffusion model. We
evaluate our approach both qualitatively and quantitatively and demonstrate
that Cloth2Tex can generate high-quality texture maps and achieve the best
visual effects in comparison to other methods. Project page:
tomguluson92.github.io/projects/cloth2tex/