Michael Möller

Orcid: 0000-0002-0492-6527

Affiliations:
  • University of Siegen, Germany
  • Technical University Munich, Department of Mathematics
  • University of Münster, Institute for Computational and Applied Mathematics


According to our database1, Michael Möller authored at least 90 papers between 2010 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Robustness and Exploration of Variational and Machine Learning Approaches to Inverse Problems: An Overview.
CoRR, 2024

2023
Preface to the Special Issue on Pattern Recognition (DAGM GCPR 2021).
Int. J. Comput. Vis., May, 2023

Temporal Action Localization for Inertial-based Human Activity Recognition.
CoRR, 2023

Kissing to Find a Match: Efficient Low-Rank Permutation Representation.
CoRR, 2023

SIGMA: Scale-Invariant Global Sparse Shape Matching.
CoRR, 2023

An Evaluation of Zero-Cost Proxies - from Neural Architecture Performance to Model Robustness.
CoRR, 2023

Differentiable Sensor Layouts for End-to-End Learning of Task-Specific Camera Parameters.
CoRR, 2023

WEAR: A Multimodal Dataset for Wearable and Egocentric Video Activity Recognition.
CoRR, 2023

Learning Posterior Distributions in Underdetermined Inverse Problems.
Proceedings of the Scale Space and Variational Methods in Computer Vision, 2023

Kissing to Find a Match: Efficient Low-Rank Permutation Representation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Evaluating Adversarial Robustness of Low dose CT Recovery.
Proceedings of the Medical Imaging with Deep Learning, 2023

QuAnt: Quantum Annealing with Learnt Couplings.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

ΣIGMA: Scale-Invariant Global Sparse Shape Matching.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

An Evaluation of Zero-Cost Proxies - From Neural Architecture Performance Prediction to Model Robustness.
Proceedings of the Pattern Recognition - 45th DAGM German Conference, 2023

CCuantuMM: Cycle-Consistent Quantum-Hybrid Matching of Multiple Shapes.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Lifting the Convex Conjugate in Lagrangian Relaxations: A Tractable Approach for Continuous Markov Random Fields.
SIAM J. Imaging Sci., September, 2022

A Generative Model for Generic Light Field Reconstruction.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Physical Representation Learning and Parameter Identification from Video Using Differentiable Physics.
Int. J. Comput. Vis., 2022

Investigating (re)current state-of-the-art in human activity recognition datasets.
Frontiers Comput. Sci., 2022

Convergent Data-driven Regularizations for CT Reconstruction.
CoRR, 2022

Deep Optimization Prior for THz Model Parameter Estimation.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Stochastic Training is Not Necessary for Generalization.
Proceedings of the Tenth International Conference on Learning Representations, 2022

FL0C: Fast L0 Cut Pursuit for Estimation of Piecewise Constant Functions.
Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

On Adversarial Robustness of Deep Image Deblurring.
Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

Non-Smooth Energy Dissipating Networks.
Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

Intrinsic Neural Fields: Learning Functions on Manifolds.
Proceedings of the Computer Vision - ECCV 2022, 2022

Explorable Data Consistent CT Reconstruction.
Proceedings of the 33rd British Machine Vision Conference 2022, 2022

A Simple Strategy to Provable Invariance via Orbit Mapping.
Proceedings of the Computer Vision - ACCV 2022, 2022

2021
Mitral Valve Segmentation Using Robust Nonnegative Matrix Factorization.
J. Imaging, 2021

Tutorial on Deep Learning for Human Activity Recognition.
CoRR, 2021

DARTS for Inverse Problems: a Study on Hyperparameter Sensitivity.
CoRR, 2021

Training or Architecture? How to Incorporate Invariance in Neural Networks.
CoRR, 2021

What Doesn't Kill You Makes You Robust(er): Adversarial Training against Poisons and Backdoors.
CoRR, 2021

Depthwise Separable Convolutions Allow for Fast and Memory-Efficient Spectral Normalization.
CoRR, 2021

Improving Deep Learning for HAR with Shallow LSTMs.
Proceedings of the ISWC 2021: Proceedings of the 2021 ACM International Symposium on Wearable Computers, 2021

Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching.
Proceedings of the 9th International Conference on Learning Representations, 2021

Learning or Modelling? An Analysis of Single Image Segmentation Based on Scribble Information.
Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

Q-Match: Iterative Shape Matching via Quantum Annealing.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Nonlinear spectral geometry processing via the TV transform.
ACM Trans. Graph., 2020

Generative Models for Generic Light Field Reconstruction.
CoRR, 2020

Inverting Gradients - How easy is it to break privacy in federated learning?
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Exploiting the Logits: Joint Sign Language Recognition and Spell-Correction.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

A Simple Domain Shifting Network for Generating Low Quality Images.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

Truth or backpropaganda? An empirical investigation of deep learning theory.
Proceedings of the 8th International Conference on Learning Representations, 2020

Learning to Identify Physical Parameters from Video Using Differentiable Physics.
Proceedings of the Pattern Recognition - 42nd DAGM German Conference, DAGM GCPR 2020, Tübingen, Germany, September 28, 2020

Fast Convex Relaxations using Graph Discretizations.
Proceedings of the 31st British Machine Vision Conference 2020, 2020

Adiabatic Quantum Graph Matching with Permutation Matrix Constraints.
Proceedings of the 8th International Conference on 3D Vision, 2020

2019
Parametric Majorization for Data-Driven Energy Minimization Methods.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Controlling Neural Networks via Energy Dissipation.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Training Auto-Encoder-Based Optimizers for Terahertz Image Reconstruction.
Proceedings of the Pattern Recognition, 2019

2018
Composite Optimization by Nonconvex Majorization-Minimization.
SIAM J. Imaging Sci., 2018

The homotopy method revisited: Computing solution paths of ℓ<sub>1</sub>-regularized problems.
Math. Comput., 2018

Convolutional Simplex Projection Network (CSPN) for Weakly Supervised Semantic Segmentation.
CoRR, 2018

Are good local minima wide in sparse recovery?
CoRR, 2018

Segmentation and Shape Extraction from Convolutional Neural Networks.
Proceedings of the 2018 IEEE Winter Conference on Applications of Computer Vision, 2018

Proximal Backpropagation.
Proceedings of the 6th International Conference on Learning Representations, 2018

Lifting Layers: Analysis and Applications.
Proceedings of the Computer Vision - ECCV 2018, 2018

DS*: Tighter Lifting-Free Convex Relaxations for Quadratic Matching Problems.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Convolutional Simplex Projection Network for Weakly Supervised Semantic Segmentation.
Proceedings of the British Machine Vision Conference 2018, 2018

2017
Tighter Lifting-Free Convex Relaxations for Quadratic Matching Problems.
CoRR, 2017

Regularized Pointwise Map Recovery from Functional Correspondence.
Comput. Graph. Forum, 2017

Nonlinear Spectral Image Fusion.
Proceedings of the Scale Space and Variational Methods in Computer Vision, 2017

Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems.
Proceedings of the IEEE International Conference on Computer Vision, 2017

Multiframe Motion Coupling for Video Super Resolution.
Proceedings of the Energy Minimization Methods in Computer Vision and Pattern Recognition, 2017

2016
Collaborative Total Variation: A General Framework for Vectorial TV Models.
SIAM J. Imaging Sci., 2016

Spectral Decompositions Using One-Homogeneous Functionals.
SIAM J. Imaging Sci., 2016

Fast sparse reconstruction: Greedy inverse scale space flows.
Math. Comput., 2016

Nonlinear Spectral Analysis via One-Homogeneous Functionals: Overview and Future Prospects.
J. Math. Imaging Vis., 2016

On the Implementation of Collaborative TV Regularization: Application to Cartoon+Texture Decomposition.
Image Process. Line, 2016

Multiframe Motion Coupling via Infimal Convolution Regularization for Video Super Resolution.
CoRR, 2016

Sublabel-Accurate Convex Relaxation of Vectorial Multilabel Energies.
Proceedings of the Computer Vision - ECCV 2016, 2016

Sublabel-Accurate Relaxation of Nonconvex Energies.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015
Variational Depth From Focus Reconstruction.
IEEE Trans. Image Process., 2015

The Primal-Dual Hybrid Gradient Method for Semiconvex Splittings.
SIAM J. Imaging Sci., 2015

Point-wise Map Recovery and Refinement from Functional Correspondence.
Proceedings of the 20th International Symposium on Vision, Modeling, and Visualization, 2015

Interactive Multi-label Segmentation of RGB-D Images.
Proceedings of the Scale Space and Variational Methods in Computer Vision, 2015

Spectral Representations of One-Homogeneous Functionals.
Proceedings of the Scale Space and Variational Methods in Computer Vision, 2015

Learning Nonlinear Spectral Filters for Color Image Reconstruction.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

2014
Color Bregman TV.
SIAM J. Imaging Sci., 2014

A framework for automated cell tracking in phase contrast microscopic videos based on normal velocities.
J. Vis. Commun. Image Represent., 2014

Low Rank Priors for Color Image Regularization.
Proceedings of the Energy Minimization Methods in Computer Vision and Pattern Recognition, 2014

A Novel Framework for Nonlocal Vectorial Total Variation Based on ℓ p, q, r -norms.
Proceedings of the Energy Minimization Methods in Computer Vision and Pattern Recognition, 2014

2013
Multiscale Methods for Polyhedral Regularizations.
SIAM J. Optim., 2013

A dual split Bregman method for fast ℓ<sup>1</sup> minimization.
Math. Comput., 2013

An adaptive inverse scale space method for compressed sensing.
Math. Comput., 2013

2012
Multiscale methods for (generalized) sparse recovery and applications in high dimensional imaging.
PhD thesis, 2012

A Convex Model for Nonnegative Matrix Factorization and Dimensionality Reduction on Physical Space.
IEEE Trans. Image Process., 2012

A Variational Approach for Sharpening High Dimensional Images.
SIAM J. Imaging Sci., 2012

The adaptive inverse scale space method for hyperspectral unmixing.
Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium, 2012

2010
An Adaptive IHS Pan-Sharpening Method.
IEEE Geosci. Remote. Sens. Lett., 2010


  Loading...