108 citations · 323 across the 11 of their papers we have counts for
3 papers · 1 filter
Surface Networks via General Covers
Niv Haim, Nimrod Segol, Heli Ben-Hamu +2
Developing deep learning techniques for geometric data is an active and fruitful research area. This paper tackles the problem of sphere-type surface learning by developing a novel…
Invariant and Equivariant Graph Networks
Haggai Maron, Heli Ben-Hamu, Nadav Shamir +1
Invariant and equivariant networks have been successfully used for learning images, sets, point clouds, and graphs. A basic challenge in developing such networks is finding the max…
Multi-chart Generative Surface Modeling
Heli Ben-Hamu, Haggai Maron, Itay Kezurer +2
This paper introduces a 3D shape generative model based on deep neural networks. A new image-like (i.e., tensor) data representation for genus-zero 3D shapes is devised. It is base…