Michael Möller

发表

Proximal Backpropagation pdf

Michael Möller, Daniel Cremers, Thomas Frerix, 2017, ICLR.

Nonlinear Spectral Image Fusion

Michael Möller, Daniel Cremers, Carola-Bibiane Schönlieb, 2017, SSVM.

Spectral Representations of One-Homogeneous Functionals

Michael Möller, Guy Gilboa, Martin Burger, 2015, SSVM.

On the Implementation of Collaborative TV Regularization: Application to Cartoon+Texture Decomposition

Michael Möller, Daniel Cremers, Catalina Sbert, 2016, Image Process. Line.

A Convex Model for Nonnegative Matrix Factorization and Dimensionality Reduction on Physical Space

Michael Möller, Jack Xin, Guillermo Sapiro, 2011, IEEE Transactions on Image Processing.

The Primal-Dual Hybrid Gradient Method for Semiconvex Splittings pdf

Michael Möller, Daniel Cremers, Thomas Möllenhoff, 2014, SIAM J. Imaging Sci..

A Novel Framework for Nonlocal Vectorial Total Variation Based on ℓ p, q, r -norms

Michael Möller, Daniel Cremers, Catalina Sbert, 2015, EMMCVPR.

Controlling Neural Networks via Energy Dissipation

Michael Möller, Daniel Cremers, Thomas Möllenhoff, 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

Sublabel–Accurate Relaxation of Nonconvex Energies

Michael Möller, Daniel Cremers, Thomas Möllenhoff, 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Multiframe Motion Coupling via Infimal Convolution Regularization for Video Super Resolution pdf

Jonas Geiping, Michael Möller, Daniel Cremers, 2016, ArXiv.

Variational Depth From Focus Reconstruction

Michael Möller, Daniel Cremers, Carola-Bibiane Schönlieb, 2014, IEEE Transactions on Image Processing.

Verfahren zum anzeigen von informationen, wobei zusatzinformationen mit digital multimedia broadcasting übertragen werden

Michael Möller, Steffen Suhr, 2000 .

Multiscale methods for (generalized) sparse recovery and applications in high dimensional imaging

Michael Möller, 2012 .

Regularized Pointwise Map Recovery from Functional Correspondence

Michael Möller, Daniel Cremers, Emanuele Rodolà, 2017, Comput. Graph. Forum.

Color Bregman TV

Michael Möller, Martin Burger, Tamara Seybold, 2013, SIAM J. Imaging Sci..

Collaborative Total Variation: A General Framework for Vectorial TV Models pdf

Michael Möller, Daniel Cremers, Catalina Sbert, 2015, SIAM J. Imaging Sci..

Multiframe Motion Coupling for Video Super Resolution

Jonas Geiping, Michael Möller, Daniel Cremers, 2016, EMMCVPR.

Fast sparse reconstruction: Greedy inverse scale space flows

Michael Möller, Xiaoqun Zhang, Xiaoqun Zhang, 2015, Math. Comput..

Point-wise Map Recovery and Refinement from Functional Correspondence

Michael Möller, Daniel Cremers, Emanuele Rodolà, 2015, VMV.

Segmentation and Shape Extraction from Convolutional Neural Networks

Michael Möller, Andreas Kolb, Volker Blanz, 2018, 2018 IEEE Winter Conference on Applications of Computer Vision (WACV).

A framework for automated cell tracking in phase contrast microscopic videos based on normal velocities

Michael Möller, Martin Burger, Peter Dieterich, 2012, J. Vis. Commun. Image Represent..

Learning Nonlinear Spectral Filters for Color Image Reconstruction

Michael Möller, Daniel Cremers, Guy Gilboa, 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

An Adaptive IHS Pan-Sharpening Method

Michael Möller, Todd Wittman, Sheida Rahmani, 2010, IEEE Geoscience and Remote Sensing Letters.

Nonlinear Spectral Analysis via One-Homogeneous Functionals: Overview and Future Prospects

Michael Möller, Guy Gilboa, Martin Burger, 2015, Journal of Mathematical Imaging and Vision.

Training Auto-encoder-based Optimizers for Terahertz Image Reconstruction

Michael Möller, Andreas Kolb, Matthias Kahl, 2019, GCPR.

Sublabel-Accurate Convex Relaxation of Vectorial Multilabel Energies

Michael Möller, Daniel Cremers, Thomas Möllenhoff, 2016, ECCV.

A dual split Bregman method for fast ℓ1 minimization

Michael Möller, Yi Yang, Stanley Osher, 2013, Math. Comput..

The adaptive inverse scale space method for hyperspectral unmixing

Michael Möller, 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium.

Multiscale Methods for Polyhedral Regularizations

Michael Möller, Martin Burger, 2013, SIAM J. Optim..

Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems

Michael Möller, Daniel Cremers, Tim Meinhardt, 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

DS*: Tighter Lifting-Free Convex Relaxations for Quadratic Matching Problems

Michael Möller, Christian Theobalt, Florian Bernard, 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Low Rank Priors for Color Image Regularization

Michael Möller, Daniel Cremers, Thomas Möllenhoff, 2015, EMMCVPR.

A Variational Approach for Sharpening High Dimensional Images

Michael Möller, Martin Burger, Andrea L. Bertozzi, 2012, SIAM J. Imaging Sci..

Spectral Decompositions Using One-Homogeneous Functionals pdf

Michael Möller, Daniel Cremers, Guy Gilboa, 2016, SIAM J. Imaging Sci..

The homotopy method revisited: Computing solution paths of ℓ1-regularized problems

Michael Möller, Daniel Cremers, Felix Krahmer, 2016, Math. Comput..

Interactive Multi-label Segmentation of RGB-D Images

Michael Möller, Daniel Cremers, Caner Hazirbas, 2015, SSVM.

An adaptive inverse scale space method for compressed sensing

Michael Möller, Stanley Osher, Martin Burger, 2012, Math. Comput..

A Convex Model for Matrix Factorization and Dimensionality Reduction on Physical Space and Its Application to Blind Hyperspectral Unmixing

Michael Möller, Jack Xin, Guillermo Sapiro, 2010 .