Geodesic convolutional neural networks on Riemannian manifolds

26 January 2015

Papers citing "Geodesic convolutional neural networks on Riemannian manifolds"

8 / 8 papers shown

Title
Flow-based Generative Models for Learning Manifold to Manifold Mappings Xingjian Zhen Rudrasis Chakraborty Liu Yang Vikas Singh DRL MedIm 31 9 0 18 Dec 2020
HexagDLy - Processing hexagonally sampled data with CNNs in PyTorch C. Steppa T. Holch 24 37 0 05 Mar 2019
Parallel Transport Convolution: A New Tool for Convolutional Neural Networks on Manifolds Stefan C. Schonsheck Bin Dong Rongjie Lai 26 22 0 21 May 2018
Learning quadrangulated patches for 3D shape parameterization and completion Kripasindhu Sarkar Kiran Varanasi D. Stricker 3DV 18 24 0 20 Sep 2017
Learning Local Receptive Fields and their Weight Sharing Scheme on Graphs Jean-Charles Vialatte Vincent Gripon G. Coppin 19 5 0 08 Jun 2017
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering M. Defferrard Xavier Bresson P. Vandergheynst GNN 102 7,587 0 30 Jun 2016
Learning shape correspondence with anisotropic convolutional neural networks Davide Boscaini Jonathan Masci Emanuele Rodolà M. Bronstein 3DPC 26 505 0 20 May 2016
Molecular Graph Convolutions: Moving Beyond Fingerprints S. Kearnes Kevin McCloskey Marc Berndl Vijay S. Pande Patrick F. Riley GNN 52 1,436 0 02 Mar 2016