Lifting the Convex Conjugate in Lagrangian Relaxations: A Tractable
Approach for Continuous Markov Random Fields

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Lifting the Convex Conjugate in Lagrangian Relaxations: A Tractable Approach for Continuous Markov Random Fields

13 July 2021

Hartmut Bauermeister

Thomas Möllenhoff

Michael Moeller

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Papers citing "Lifting the Convex Conjugate in Lagrangian Relaxations: A Tractable Approach for Continuous Markov Random Fields"

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Title
Lasry-Lions Envelopes and Nonconvex Optimization: A Homotopy Approach M. Simões Andreas Themelis Panagiotis Patrinos 22 3 0 15 Mar 2021
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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 15 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 33 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