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

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
ArXivPDFHTML

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

2 / 2 papers shown
Title
TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view
  Stereo
TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo
Lukas Koestler
Nan Yang
Niclas Zeller
Daniel Cremers
MDE
61
68
0
14 Nov 2021
Unsupervised Dense Shape Correspondence using Heat Kernels
Unsupervised Dense Shape Correspondence using Heat Kernels
Mehmet Aygün
Zorah Lähner
Daniel Cremers
38
15
0
23 Oct 2020
1