SNUG: Self-Supervised Neural Dynamic Garments

We present a self-supervised method to learn dynamic 3D deformations of garments worn by parametric human bodies. State-of-the-art data-driven approaches to model 3D garment deformations are trained using supervised strategies that require large datasets, usually obtained by expensive physics-based simulation methods or professional multi-camera capture setups.

2022: I. Santesteban, M. Otaduy, D. Casas

https://arxiv.org/pdf/2204.02219v1.pdf