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Self-Supervised Collision Handling via Generative 3D Garment Models for Virtual Try-On
2021
Zenodo
We propose a new generative model for 3D garment deformations that enables us to learn, for the first time, a data-driven method for virtual try-on that effectively addresses garment-body collisions. In contrast to existing methods that require an undesirable postprocessing step to fix garment-body interpenetrations at test time, our approach directly outputs 3D garment configurations that do not collide with the underlying body. Key to our success is a new canonical space for garments that
doi:10.5281/zenodo.5595961
fatcat:tmku2entezbpla2cpk2guuxqja