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Unsupervised Dense Shape Correspondence using Heat Kernels

Unsupervised Dense Shape Correspondence using Heat Kernels

23 October 2020
Mehmet Aygün
Zorah Lähner
Daniel Cremers
ArXivPDFHTML

Papers citing "Unsupervised Dense Shape Correspondence using Heat Kernels"

4 / 4 papers shown
Title
Deep Orientation-Aware Functional Maps: Tackling Symmetry Issues in
  Shape Matching
Deep Orientation-Aware Functional Maps: Tackling Symmetry Issues in Shape Matching
Nicolas Donati
E. Corman
M. Ovsjanikov
19
34
0
28 Apr 2022
Learning Spectral Unions of Partial Deformable 3D Shapes
Learning Spectral Unions of Partial Deformable 3D Shapes
Luca Moschella
Simone Melzi
Luca Cosmo
Filippo Maggioli
Or Litany
M. Ovsjanikov
Leonidas J. Guibas
Emanuele Rodolà
24
7
0
31 Mar 2021
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
126
325
0
13 Jun 2018
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
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