Computer Graphics
TU Braunschweig

Tex2Shape: Detailed Full Human Body Geometry from a Single Image


Tex2Shape: Detailed Full Human Body Geometry from a Single Image

We present a simple yet effective method to infer detailed full human body shape from only a single photograph. Our model can infer full-body shape including face, hair, and clothing including wrinkles at interactive frame-rates. Results feature details even on parts that are occluded in the input image. Our main idea is to turn shape regression into an aligned image-to-image translation problem. The input to our method is a partial texture map of the visible region obtained from off-the-shelf methods. From a partial texture, we estimate detailed normal and vector displacement maps, which can be applied to a low-resolution smooth body model to add detail and clothing. Despite being trained purely with synthetic data, our model generalizes well to real-world photographs. Numerous results demonstrate the versatility and robustness of our method.


Author(s):Thiemo Alldieck, Gerard Pons-Moll, Christian Theobalt, Marcus Magnor
Published:April 2019
Type:Misc
Howpublished:arXiv preprint
Project(s): Comprehensive Human Performance Capture from Monocular Video Footage 


@misc{alldieck2019tex2shape,
  title = {Tex2Shape: Detailed Full Human Body Geometry from a Single Image},
  author = {Alldieck, Thiemo and Pons-Moll, Gerard and Theobalt, Christian and Magnor, Marcus},
  howpublished = {arXiv preprint},
  month = {Apr},
  year = {2019}
}

Authors