Michael Möller

ORCID

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 63

Top Venues

University of Münster (PHD)

Education History

University of Münster

PHD

Publications

Andreas Görlitz, Michael Möller, Andreas Kolb
Coherent Enhancement of Depth Images and Normal Maps Using Second-Order Geometric Models on Weighted Finite Graphs. 3DV (2024)
Jovita Lukasik, Michael Möller, Margret Keuper
An Evaluation of Zero-Cost Proxies - from Neural Architecture Performance to Model Robustness. CoRR (2023)
Christina Runkel, Michael Möller, Carola-Bibiane Schönlieb, Christian Etmann
Learning Posterior Distributions in Underdetermined Inverse Problems. SSVM (2023)
Maolin Gao, Paul Roetzer, Marvin Eisenberger, Zorah Lähner, Michael Möller, Daniel Cremers, Florian Bernard
ΣIGMA: Scale-Invariant Global Sparse Shape Matching. ICCV (2023)
Hannah Dröge, Zorah Lähner, Yuval Bahat, Onofre Martorell, Felix Heide, Michael Möller
Kissing to Find a Match: Efficient Low-Rank Permutation Representation. CoRR (2023)
Maolin Gao, Paul Roetzer, Marvin Eisenberger, Zorah Lähner, Michael Möller, Daniel Cremers, Florian Bernard
SIGMA: Scale-Invariant Global Sparse Shape Matching. CoRR (2023)
Kanchana Vaishnavi Gandikota, Paramanand Chandramouli, Hannah Dröge, Michael Möller
Evaluating Adversarial Robustness of Low dose CT Recovery. MIDL (2023)
Christian Bauckhage, Wolfgang Förstner, Juergen Gall, Michael Möller, Alexander G. Schwing
Preface to the Special Issue on Pattern Recognition (DAGM GCPR 2021). Int. J. Comput. Vis. 131 (5) (2023)
Marius Bock, Michael Möller, Kristof Van Laerhoven
Temporal Action Localization for Inertial-based Human Activity Recognition. CoRR (2023)
Kanchana Vaishnavi Gandikota, Paramanand Chandramouli, Michael Möller
On Adversarial Robustness of Deep Image Deblurring. ICIP (2022)
Rama Krishna Kandukuri, Jan Achterhold, Michael Möller, Joerg Stueckler
Physical Representation Learning and Parameter Identification from Video Using Differentiable Physics. Int. J. Comput. Vis. 130 (1) (2022)
Kanchana Vaishnavi Gandikota, Jonas Geiping, Zorah Lähner, Adam Czaplinski, Michael Möller
A Simple Strategy to Provable Invariance via Orbit Mapping. ACCV (5) (2022)
Paramanand Chandramouli, Kanchana Vaishnavi Gandikota, Andreas Görlitz, Andreas Kolb, Michael Möller
A Generative Model for Generic Light Field Reconstruction. IEEE Trans. Pattern Anal. Mach. Intell. 44 (4) (2022)
Tak Ming Wong, Hartmut Bauermeister, Matthias Kahl, Peter Haring Bolívar, Michael Möller, Andreas Kolb
Deep Optimization Prior for THz Model Parameter Estimation. WACV (2022)
Hannah Dröge, Thomas Möllenhoff, Michael Möller
Non-Smooth Energy Dissipating Networks. ICIP (2022)
Kanchana Vaishnavi Gandikota, Jonas Geiping, Zorah Lähner, Adam Czaplinski, Michael Möller
A Simple Strategy to Provable Invariance via Orbit Mapping. CoRR (2022)
Marius Bock, Alexander Hölzemann, Michael Möller, Kristof Van Laerhoven
Investigating (re)current state-of-the-art in human activity recognition datasets. Frontiers Comput. Sci. 4 (2022)
Andreas Görlitz, Michael Möller, Andreas Kolb
FL0C: Fast L0 Cut Pursuit for Estimation of Piecewise Constant Functions. ICIP (2022)
Lukas Koestler, Daniel Grittner, Michael Möller, Daniel Cremers, Zorah Lähner
Intrinsic Neural Fields: Learning Functions on Manifolds. CoRR (2022)
Hartmut Bauermeister, Emanuel Laude, Thomas Möllenhoff, Michael Möller, Daniel Cremers
Lifting the Convex Conjugate in Lagrangian Relaxations: A Tractable Approach for Continuous Markov Random Fields. SIAM J. Imaging Sci. 15 (3) (2022)
Lukas Koestler, Daniel Grittner, Michael Möller, Daniel Cremers, Zorah Lähner
Intrinsic Neural Fields: Learning Functions on Manifolds. ECCV (2) (2022)
Marcel Seelbach Benkner, Zorah Lähner, Vladislav Golyanik, Christof Wunderlich, Christian Theobalt, Michael Möller
Q-Match: Iterative Shape Matching via Quantum Annealing. CoRR (2021)
Hannah Dröge, Baichuan Yuan, Rafael Llerena, Jesse T. Yen, Michael Möller, Andrea L. Bertozzi
Mitral Valve Segmentation Using Robust Nonnegative Matrix Factorization. J. Imaging 7 (10) (2021)
Hartmut Bauermeister, Emanuel Laude, Thomas Möllenhoff, Michael Möller, Daniel Cremers
Lifting the Convex Conjugate in Lagrangian Relaxations: A Tractable Approach for Continuous Markov Random Fields. CoRR (2021)
Kanchana Vaishnavi Gandikota, Jonas Geiping, Zorah Lähner, Adam Czaplinski, Michael Möller
Training or Architecture? How to Incorporate Invariance in Neural Networks. CoRR (2021)
Christina Runkel, Christian Etmann, Michael Möller, Carola-Bibiane Schönlieb
Depthwise Separable Convolutions Allow for Fast and Memory-Efficient Spectral Normalization. CoRR (2021)
Marius Bock, Alexander Hölzemann, Michael Möller, Kristof Van Laerhoven
Tutorial on Deep Learning for Human Activity Recognition. CoRR (2021)
Hannah Dröge, Michael Möller
Learning or Modelling? An Analysis of Single Image Segmentation Based on Scribble Information. ICIP (2021)
Christina Runkel, Stefan Dorenkamp, Hartmut Bauermeister, Michael Möller
Exploiting the Logits: Joint Sign Language Recognition and Spell-Correction. ICPR (2020)
Rama Krishna Kandukuri, Jan Achterhold, Michael Möller, Jörg Stückler
Learning to Identify Physical Parameters from Video Using Differentiable Physics. CoRR (2020)
Marco Fumero, Michael Möller, Emanuele Rodolà
Nonlinear spectral geometry processing via the TV transform. ACM Trans. Graph. 39 (6) (2020)
Rama Krishna Kandukuri, Jan Achterhold, Michael Möller, Joerg Stueckler
Learning to Identify Physical Parameters from Video Using Differentiable Physics. GCPR (2020)
Marco Fumero, Michael Möller, Emanuele Rodolà
Nonlinear Spectral Geometry Processing via the TV Transform. CoRR (2020)
Tak Ming Wong, Matthias Kahl, Peter Haring Bolívar, Andreas Kolb, Michael Möller
Training Auto-Encoder-Based Optimizers for Terahertz Image Reconstruction. GCPR (2019)
Michael Möller, Thomas Möllenhoff, Daniel Cremers
Controlling Neural Networks via Energy Dissipation. CoRR (2019)
Tak Ming Wong, Matthias Kahl, Peter Haring Bolívar, Andreas Kolb, Michael Möller
Training Auto-encoder-based Optimizers for Terahertz Image Reconstruction. CoRR (2019)
Michael Möller, Thomas Möllenhoff, Daniel Cremers
Controlling Neural Networks via Energy Dissipation. ICCV (2019)
Peter Ochs, Tim Meinhardt, Laura Leal-Taixé, Michael Möller
Lifting Layers: Analysis and Applications. CoRR (2018)
Peter Ochs, Tim Meinhardt, Laura Leal-Taixé, Michael Möller
Lifting Layers: Analysis and Applications. ECCV (1) (2018)
Jonas Geiping, Michael Möller
Composite Optimization by Nonconvex Majorization-Minimization. CoRR (2018)
Thomas Frerix, Thomas Möllenhoff, Michael Möller, Daniel Cremers
Proximal Backpropagation. ICLR (Poster) (2018)
Florian Bernard, Christian Theobalt, Michael Möller
DS*: Tighter Lifting-Free Convex Relaxations for Quadratic Matching Problems. CVPR (2018)
Jonas Geiping, Michael Möller
Composite Optimization by Nonconvex Majorization-Minimization. SIAM J. Imaging Sci. 11 (4) (2018)
Mai Lan Ha, Gianni Franchi, Michael Möller, Andreas Kolb, Volker Blanz
Segmentation and Shape Extraction from Convolutional Neural Networks. WACV (2018)
Björn Bringmann, Daniel Cremers, Felix Krahmer, Michael Möller
-regularized problems. Math. Comput. 87 (313) (2018)
Emanuele Rodolà, Michael Möller, Daniel Cremers
Regularized Pointwise Map Recovery from Functional Correspondence. Comput. Graph. Forum 36 (8) (2017)
Tim Meinhardt, Michael Möller, Caner Hazirbas, Daniel Cremers
Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems. ICCV (2017)
Martin Benning, Michael Möller, Raz Z. Nossek, Martin Burger, Daniel Cremers, Guy Gilboa, Carola-Bibiane Schönlieb
Nonlinear Spectral Image Fusion. CoRR (2017)
Florian Bernard, Christian Theobalt, Michael Möller
Tighter Lifting-Free Convex Relaxations for Quadratic Matching Problems. CoRR (2017)
Martin Benning, Michael Möller, Raz Z. Nossek, Martin Burger, Daniel Cremers, Guy Gilboa, Carola-Bibiane Schönlieb
Nonlinear Spectral Image Fusion. SSVM (2017)
Thomas Frerix, Thomas Möllenhoff, Michael Möller, Daniel Cremers
Proximal Backpropagation. CoRR (2017)
Tim Meinhardt, Michael Möller, Caner Hazirbas, Daniel Cremers
Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems. CoRR (2017)
Jonas Geiping, Hendrik Dirks, Daniel Cremers, Michael Möller
Multiframe Motion Coupling for Video Super Resolution. EMMCVPR (2017)
Guy Gilboa, Michael Möller, Martin Burger
Nonlinear Spectral Analysis via One-Homogeneous Functionals: Overview and Future Prospects. J. Math. Imaging Vis. 56 (2) (2016)
Hendrik Dirks, Jonas Geiping, Daniel Cremers, Michael Möller
Multiframe Motion Coupling via Infimal Convolution Regularization for Video Super Resolution. CoRR (2016)
Joan Duran, Michael Möller, Catalina Sbert, Daniel Cremers
On the Implementation of Collaborative TV Regularization: Application to Cartoon+Texture Decomposition. Image Process. Line 6 (2016)
Emanuel Laude, Thomas Möllenhoff, Michael Möller, Jan Lellmann, Daniel Cremers
Sublabel-Accurate Convex Relaxation of Vectorial Multilabel Energies. CoRR (2016)
Martin Burger, Guy Gilboa, Michael Möller, Lina Eckardt, Daniel Cremers
Spectral Decompositions using One-Homogeneous Functionals. CoRR (2016)
Thomas Möllenhoff, Emanuel Laude, Michael Möller, Jan Lellmann, Daniel Cremers
Sublabel-Accurate Relaxation of Nonconvex Energies. CVPR (2016)
Emanuel Laude, Thomas Möllenhoff, Michael Möller, Jan Lellmann, Daniel Cremers
Sublabel-Accurate Convex Relaxation of Vectorial Multilabel Energies. ECCV (1) (2016)
Michael Möller, Xiaoqun Zhang
Fast sparse reconstruction: Greedy inverse scale space flows. Math. Comput. 85 (297) (2016)
Joan Duran, Michael Möller, Catalina Sbert, Daniel Cremers
Collaborative Total Variation: A General Framework for Vectorial TV Models. SIAM J. Imaging Sci. 9 (1) (2016)
Martin Burger, Guy Gilboa, Michael Möller, Lina Eckardt, Daniel Cremers
Spectral Decompositions Using One-Homogeneous Functionals. SIAM J. Imaging Sci. 9 (3) (2016)
Michael Möller, Martin Benning, Carola Schönlieb, Daniel Cremers
Variational Depth From Focus Reconstruction. IEEE Trans. Image Process. 24 (12) (2015)
Michael Möller, Julia Diebold, Guy Gilboa, Daniel Cremers
Learning Nonlinear Spectral Filters for Color Image Reconstruction. ICCV (2015)
Thomas Möllenhoff, Evgeny Strekalovskiy, Michael Möller, Daniel Cremers
The Primal-Dual Hybrid Gradient Method for Semiconvex Splittings. SIAM J. Imaging Sci. 8 (2) (2015)
Joan Duran, Michael Möller, Catalina Sbert, Daniel Cremers
Collaborative Total Variation: A General Framework for Vectorial TV Models. CoRR (2015)
Martin Burger, Lina Eckardt, Guy Gilboa, Michael Möller
Spectral Representations of One-Homogeneous Functionals. SSVM (2015)
Emanuele Rodolà, Michael Möller, Daniel Cremers
Point-wise Map Recovery and Refinement from Functional Correspondence. CoRR (2015)
Thomas Möllenhoff, Emanuel Laude, Michael Möller, Jan Lellmann, Daniel Cremers
Sublabel-Accurate Relaxation of Nonconvex Energies. CoRR (2015)
Julia Diebold, Nikolaus Demmel, Caner Hazirbas, Michael Möller, Daniel Cremers
Interactive Multi-label Segmentation of RGB-D Images. SSVM (2015)
Guy Gilboa, Michael Möller, Martin Burger
Nonlinear Spectral Analysis via One-homogeneous Functionals - Overview and Future Prospects. CoRR (2015)
Emanuele Rodolà, Michael Möller, Daniel Cremers
Point-wise Map Recovery and Refinement from Functional Correspondence. VMV (2015)
Joan Duran, Michael Möller, Catalina Sbert, Daniel Cremers
A Novel Framework for Nonlocal Vectorial Total Variation Based on ℓ p, q, r -norms. EMMCVPR (2014)
Thomas Möllenhoff, Evgeny Strekalovskiy, Michael Möller, Daniel Cremers
The Primal-Dual Hybrid Gradient Method for Semiconvex Splittings. CoRR (2014)
Michael Möller, Eva-Maria Brinkmann, Martin Burger, Tamara Seybold
Color Bregman TV. SIAM J. Imaging Sci. 7 (4) (2014)
Michael Möller, Martin Benning, Carola-Bibiane Schönlieb, Daniel Cremers
Variational Depth from Focus Reconstruction. CoRR (2014)
Michael Möller, Martin Burger, Peter Dieterich, Albrecht Schwab
A framework for automated cell tracking in phase contrast microscopic videos based on normal velocities. J. Vis. Commun. Image Represent. 25 (2) (2014)
Thomas Möllenhoff, Evgeny Strekalovskiy, Michael Möller, Daniel Cremers
Low Rank Priors for Color Image Regularization. EMMCVPR (2014)
Michael Möller, Martin Burger
Multiscale Methods for Polyhedral Regularizations. SIAM J. Optim. 23 (3) (2013)
Martin Burger, Michael Möller, Martin Benning, Stanley J. Osher
An adaptive inverse scale space method for compressed sensing. Math. Comput. 82 (281) (2013)
Yi Yang, Michael Möller, Stanley J. Osher
minimization. Math. Comput. 82 (284) (2013)
Michael Möller
The adaptive inverse scale space method for hyperspectral unmixing. IGARSS (2012)
Michael Möller, Todd Wittman, Andrea L. Bertozzi, Martin Burger
A Variational Approach for Sharpening High Dimensional Images. SIAM J. Imaging Sci. 5 (1) (2012)
Ernie Esser, Michael Möller, Stanley J. Osher, Guillermo Sapiro, Jack Xin
A Convex Model for Nonnegative Matrix Factorization and Dimensionality Reduction on Physical Space. IEEE Trans. Image Process. 21 (7) (2012)
Michael Möller, Martin Burger, Peter Dieterich, Albrecht Schwab
A Framework for Automated Cell Tracking in Phase Contrast Microscopic Videos based on Normal Velocities CoRR (2012)
Sheida Rahmani, Melissa Strait, Daria Merkurjev, Michael Möller, Todd Wittman
An Adaptive IHS Pan-Sharpening Method. IEEE Geosci. Remote. Sens. Lett. 7 (4) (2010)

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Publication Activity (10 Years)

Top Topics

Top Venues

Michael Möller