22 citations · 64 across the 12 of their papers we have counts for
5 papers · 1 filter
Fast Encoder-Based 3D from Casual Videos via Point Track Processing
Yoni Kasten, Wuyue Lu, Haggai Maron
This paper addresses the long-standing challenge of reconstructing 3D structures from videos with dynamic content. Current approaches to this problem were not designed to operate o…
Deep Permutation Equivariant Structure from Motion
Dror Moran, Hodaya Koslowsky, Yoni Kasten +3
Existing deep methods produce highly accurate 3D reconstructions in stereo and multiview stereo settings, i.e., when cameras are both internally and externally calibrated. Neverthe…
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…
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…
Point Convolutional Neural Networks by Extension Operators
Matan Atzmon, Haggai Maron, Yaron Lipman
This paper presents Point Convolutional Neural Networks (PCNN): a novel framework for applying convolutional neural networks to point clouds. The framework consists of two operator…