ContourCraft: Learning to Resolve Intersections in Neural Multi-Garment Simulations

arXiv:2405.09522v1 Announce Type: cross
Abstract: Learning-based approaches to cloth simulation have started to show their potential in recent years. However, handling collisions and intersections in neural simulations remains a largely unsolved problem. In this work, we present \moniker{}, a learning-based solution for handling intersections in neural cloth simulations. Unlike conventional approaches that critically rely on intersection-free inputs, \moniker{} robustly recovers from intersections introduced through missed collisions, self-penetrating bodies, or errors in manually designed multi-layer outfits. The technical core of \moniker{} …

abstract arxiv cs.gr cs.lg however show simulation simulations solution type unsolved work