Revisiting Map Relations for Unsupervised Non-Rigid Shape Matching

ArXi:2310.11420v2 Announce Type: replace We propose a novel unsupervised learning approach for non-rigid 3D shape matching. Our approach improves upon recent state-of-the art deep functional map methods and can be applied to a broad range of different challenging scenarios. Previous deep functional map methods mainly focus on feature extraction and aim exclusively at obtaining expressive features for functional map computation.