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Field Convolutions for Surface CNNs

Field Convolutions for Surface CNNs

8 April 2021
Thomas W. Mitchel
Vladimir G. Kim
Michael Kazhdan
ArXivPDFHTML

Papers citing "Field Convolutions for Surface CNNs"

6 / 6 papers shown
Title
Toward Mesh-Invariant 3D Generative Deep Learning with Geometric
  Measures
Toward Mesh-Invariant 3D Generative Deep Learning with Geometric Measures
T. Besnier
Sylvain Arguillere
E. Pierson
Mohamed Daoudi
3DH
16
8
0
27 Jun 2023
SRFeat: Learning Locally Accurate and Globally Consistent Non-Rigid
  Shape Correspondence
SRFeat: Learning Locally Accurate and Globally Consistent Non-Rigid Shape Correspondence
Lei Li
Souhaib Attaiki
M. Ovsjanikov
19
8
0
16 Sep 2022
Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric
  graphs
Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs
P. D. Haan
Maurice Weiler
Taco S. Cohen
Max Welling
100
127
0
11 Mar 2020
3D-CODED : 3D Correspondences by Deep Deformation
3D-CODED : 3D Correspondences by Deep Deformation
Thibault Groueix
Matthew Fisher
Vladimir G. Kim
Bryan C. Russell
Mathieu Aubry
3DPC
3DV
115
325
0
13 Jun 2018
PointNet: Deep Learning on Point Sets for 3D Classification and
  Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
C. Qi
Hao Su
Kaichun Mo
Leonidas J. Guibas
3DH
3DPC
3DV
PINN
222
14,099
0
02 Dec 2016
Geometric deep learning on graphs and manifolds using mixture model CNNs
Geometric deep learning on graphs and manifolds using mixture model CNNs
Federico Monti
Davide Boscaini
Jonathan Masci
Emanuele Rodolà
Jan Svoboda
M. Bronstein
GNN
251
1,811
0
25 Nov 2016
1