Vid2Avatar: 3D Avatar Reconstruction from Videos in the Wild via Self-supervised Scene Decomposition

Figure 1 . We propose Vid2Avatar, a method to reconstruct detailed 3D avatars from monocular videos in the wild via self-supervised scene decomposition. Our method does not require any groundtruth supervision or priors extracted from large datasets of clothed human scans, nor do we rely on any external segmentation modules. Project page: https://ait.ethz.ch/vid2avatar .