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2107.06028
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Lifting the Convex Conjugate in Lagrangian Relaxations: A Tractable Approach for Continuous Markov Random Fields
13 July 2021
Hartmut Bauermeister
Emanuel Laude
Thomas Möllenhoff
Michael Moeller
Daniel Cremers
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Papers citing
"Lifting the Convex Conjugate in Lagrangian Relaxations: A Tractable Approach for Continuous Markov Random Fields"
16 / 16 papers shown
Title
Lasry-Lions Envelopes and Nonconvex Optimization: A Homotopy Approach
M. Simões
Andreas Themelis
Panagiotis Patrinos
20
3
0
15 Mar 2021
Non-Rigid Puzzles
Or Litany
Emanuele Rodolà
Alexander M. Bronstein
Michael M. Bronstein
Daniel Cremers
3DV
35
77
0
26 Nov 2020
Unsupervised Dense Shape Correspondence using Heat Kernels
Mehmet Aygün
Zorah Lähner
Daniel Cremers
75
16
0
23 Oct 2020
Learning Monocular 3D Vehicle Detection without 3D Bounding Box Labels
Lukas Koestler
Nan Yang
Rui Wang
Daniel Cremers
3DPC
50
9
0
07 Oct 2020
On the Connection between Dynamical Optimal Transport and Functional Lifting
Thomas Vogt
Roland Haase
D. Bednarski
J. Lellmann
13
4
0
06 Jul 2020
Inferring Super-Resolution Depth from a Moving Light-Source Enhanced RGB-D Sensor: A Variational Approach
Lu Sang
Bjoern Haefner
Daniel Cremers
3DV
MDE
64
11
0
13 Dec 2019
Sparse Surface Constraints for Combining Physics-based Elasticity Simulation and Correspondence-Free Object Reconstruction
S. Weiss
Robert Maier
Rüdiger Westermann
Daniel Cremers
Nils Thuerey
57
17
0
04 Oct 2019
Lifting Vectorial Variational Problems: A Natural Formulation based on Geometric Measure Theory and Discrete Exterior Calculus
Thomas Möllenhoff
Daniel Cremers
31
13
0
02 May 2019
Photometric Depth Super-Resolution
Bjoern Haefner
Songyou Peng
Alok Verma
Yvain Quéau
Daniel Cremers
SupR
MDE
74
27
0
26 Sep 2018
q-Space Novelty Detection with Variational Autoencoders
A. Vasilev
Vladimir Golkov
Marc Meissner
I. Lipp
Eleonora Sgarlata
V. Tomassini
Derek K. Jones
Daniel Cremers
DRL
53
59
0
08 Jun 2018
Associative Domain Adaptation
Philip Häusser
Thomas Frerix
A. Mordvintsev
Daniel Cremers
BDL
69
243
0
02 Aug 2017
Learning by Association - A versatile semi-supervised training method for neural networks
Philip Häusser
A. Mordvintsev
Daniel Cremers
BDL
70
121
0
03 Jun 2017
Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems
Tim Meinhardt
Michael Möller
C. Hazirbas
Daniel Cremers
63
356
0
11 Apr 2017
Multi-View Deep Learning for Consistent Semantic Mapping with RGB-D Cameras
Lingni Ma
J. Stückler
C. Kerl
Daniel Cremers
52
152
0
26 Mar 2017
Image-based localization using LSTMs for structured feature correlation
F. Walch
C. Hazirbas
Laura Leal-Taixé
Torsten Sattler
S. Hilsenbeck
Daniel Cremers
70
496
0
23 Nov 2016
Sublabel-Accurate Relaxation of Nonconvex Energies
Thomas Möllenhoff
Emanuel Laude
Michael Möller
J. Lellmann
Daniel Cremers
41
43
0
04 Dec 2015
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