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360-Degree Textures of People in Clothing from a Single Image
[article]
2019
arXiv
pre-print
In this paper we predict a full 3D avatar of a person from a single image. We infer texture and geometry in the UV-space of the SMPL model using an image-to-image translation method. Given partial texture and segmentation layout maps derived from the input view, our model predicts the complete segmentation map, the complete texture map, and a displacement map. The predicted maps can be applied to the SMPL model in order to naturally generalize to novel poses, shapes, and even new clothing. In
arXiv:1908.07117v1
fatcat:x2t53g423rbldhqdfx647m6qbe