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Unsupervised Deep Learning for Structured Shape Matching

Unsupervised Deep Learning for Structured Shape Matching

10 December 2018
Jean-Michel Roufosse
Abhishek Sharma
M. Ovsjanikov
    3DPC
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Papers citing "Unsupervised Deep Learning for Structured Shape Matching"

16 / 16 papers shown
Title
Denoising Functional Maps: Diffusion Models for Shape Correspondence
Denoising Functional Maps: Diffusion Models for Shape Correspondence
Aleksei Zhuravlev
Zorah Lähner
Vladislav Golyanik
DiffM
105
1
0
03 Mar 2025
Forecasting Sequential Data using Consistent Koopman Autoencoders
Forecasting Sequential Data using Consistent Koopman Autoencoders
Omri Azencot
N. Benjamin Erichson
Vanessa Lin
Michael W. Mahoney
AI4TS
AI4CE
109
149
0
04 Mar 2020
Self-supervised Learning of Dense Shape Correspondence
Self-supervised Learning of Dense Shape Correspondence
Oshri Halimi
Or Litany
Emanuele Rodolà
A. Bronstein
Ron Kimmel
3DPC
39
23
0
06 Dec 2018
Multi-directional Geodesic Neural Networks via Equivariant Convolution
Multi-directional Geodesic Neural Networks via Equivariant Convolution
A. Poulenard
M. Ovsjanikov
3DH
41
90
0
01 Oct 2018
Continuous and Orientation-preserving Correspondences via Functional
  Maps
Continuous and Orientation-preserving Correspondences via Functional Maps
Jing Ren
A. Poulenard
Peter Wonka
M. Ovsjanikov
29
165
0
12 Jun 2018
Efficient Deformable Shape Correspondence via Kernel Matching
Efficient Deformable Shape Correspondence via Kernel Matching
Zorah Lähner
Matthias Vestner
A. Boyarski
Or Litany
Ron Slossberg
...
Emanuele Rodolà
A. Bronstein
M. Bronstein
Ron Kimmel
Daniel Cremers
3DPC
31
120
0
25 Jul 2017
Deep Functional Maps: Structured Prediction for Dense Shape
  Correspondence
Deep Functional Maps: Structured Prediction for Dense Shape Correspondence
Or Litany
Tal Remez
Emanuele Rodolà
A. Bronstein
M. Bronstein
3DPC
110
284
0
27 Apr 2017
Product Manifold Filter: Non-Rigid Shape Correspondence via Kernel
  Density Estimation in the Product Space
Product Manifold Filter: Non-Rigid Shape Correspondence via Kernel Density Estimation in the Product Space
Matthias Vestner
R. Litman
Emanuele Rodolà
A. Bronstein
Daniel Cremers
62
130
0
03 Jan 2017
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
368
1,817
0
25 Nov 2016
Convolutional Neural Networks on Graphs with Fast Localized Spectral
  Filtering
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
M. Defferrard
Xavier Bresson
P. Vandergheynst
GNN
259
7,622
0
30 Jun 2016
Learning shape correspondence with anisotropic convolutional neural
  networks
Learning shape correspondence with anisotropic convolutional neural networks
Davide Boscaini
Jonathan Masci
Emanuele Rodolà
M. Bronstein
3DPC
123
506
0
20 May 2016
Dense Human Body Correspondences Using Convolutional Networks
Dense Human Body Correspondences Using Convolutional Networks
Lingyu Wei
Qi-Xing Huang
Duygu Ceylan
E. Vouga
Hao Li
3DH
98
206
0
18 Nov 2015
Point-wise Map Recovery and Refinement from Functional Correspondence
Point-wise Map Recovery and Refinement from Functional Correspondence
Emanuele Rodolà
Michael Möller
Daniel Cremers
34
74
0
18 Jun 2015
Functional correspondence by matrix completion
Functional correspondence by matrix completion
Artiom Kovnatsky
M. Bronstein
Xavier Bresson
P. Vandergheynst
38
90
0
27 Dec 2014
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
970
149,474
0
22 Dec 2014
Coupled quasi-harmonic bases
Coupled quasi-harmonic bases
Artiom Kovnatsky
M. Bronstein
A. Bronstein
K. Glashoff
Ron Kimmel
88
200
0
28 Sep 2012
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