Developers Igor Santesteban, Miguel A. Otaduy, and Dan Casas have introduced SNUG, a new neural network for adding 3D deformations to outfits worn by parametric human bodies. According to the team, the network was trained by using a new training scheme that removes the need for ground-truth samples, enabling self-supervised training of dynamic 3D garment deformations. The method they used allowed them to interactively manipulate the shape parameter of the subject, while producing highly realistic garment deformations, without using any supervision during train time.
