SPA-VAE: Similar-Parts-Assignment for Unsupervised 3D Point Cloud Generation. (arXiv:2203.07825v2 [cs.CV] UPDATED)

This paper addresses the problem of unsupervised parts-aware point cloud
generation with learned parts-based self-similarity. Our SPA-VAE infers a set
of latent canonical candidate shapes for any given object, along with a set of
rigid body transformations for each such candidate shape to one or more
locations within the assembled object. In this way, noisy samples on the
surface of, say, each leg of a table, are effectively combined to estimate a
single leg prototype. When parts-based self-similarity exists in …

arxiv cloud generation spa unsupervised