3 papers
cs.CV2020
Computational Analysis of Deformable Manifolds: from Geometric Modelling to Deep Learning
Stefan C Schonsheck
Leo Tolstoy opened his monumental novel Anna Karenina with the now famous words: Happy families are all alike; every unhappy family is unhappy in its own way A similar notion also…
cs.CV2020
Unsupervised Geometric Disentanglement for Surfaces via CFAN-VAE
N. Joseph Tatro, Stefan C. Schonsheck, Rongjie Lai
Geometric disentanglement, the separation of latent codes for intrinsic (i.e. identity) and extrinsic(i.e. pose) geometry, is a prominent task for generative models of non-Euclidea…
cs.LG2019
Chart Auto-Encoders for Manifold Structured Data
Stefan Schonsheck, Jie Chen, Rongjie Lai
Deep generative models have made tremendous advances in image and signal representation learning and generation. These models employ the full Euclidean space or a bounded subset as…