| The natural vectorial total variation which arises from geometric measure theory B Goldluecke, E Strekalovskiy, D Cremers SIAM Journal on Imaging Sciences 5 (2), 537-563, 2012 | 147 | 2012 |
| Total Variation Regularization for Functions with Values in a Manifold J Lellmann, E Strekalovskiy, S Koetter, D Cremers International Conference on Computer Vision (ICCV), 2013 | 94 | 2013 |
| Real-Time Minimization of the Piecewise Smooth Mumford-Shah Functional E Strekalovskiy, D Cremers European Conference on Computer Vision (ECCV), 127-141, 2014 | 73 | 2014 |
| The Primal-Dual Hybrid Gradient Method for Semiconvex Splittings T Möllenhoff, E Strekalovskiy, M Moeller, D Cremers arXiv preprint arXiv:1407.1723, 2014 | 71 | 2014 |
| Generalized ordering constraints for multilabel optimization E Strekalovskiy, D Cremers International Conference on Computer Vision (ICCV), 2011 | 62 | 2011 |
| A convex representation for the vectorial Mumford-Shah functional E Strekalovskiy, A Chambolle, D Cremers Computer Vision and Pattern Recognition (CVPR), IEEE Conference on, 2012 | 51 | 2012 |
| Total cyclic variation and generalizations D Cremers, E Strekalovskiy Journal of Mathematical Imaging and Vision 47 (3), 258-277, 2012 | 47 | 2012 |
| Total variation for cyclic structures: Convex relaxation and efficient minimization E Strekalovskiy, D Cremers Computer Vision and Pattern Recognition (CVPR), 2011 | 45 | 2011 |
| Tight convex relaxations for vector-valued labeling problems E Strekalovskiy, B Goldluecke, D Cremers International Conference on Computer Vision (ICCV), 2011 | 41 | 2011 |
| Tight convex relaxations for vector-valued labeling B Goldluecke, E Strekalovskiy, D Cremers SIAM Journal on Imaging Science 6 (3), 1626–1664, 2013 | 38 | 2013 |
| Convex relaxation of vectorial problems with coupled regularization E Strekalovskiy, A Chambolle, D Cremers SIAM Journal on Imaging Sciences, 2014 | 35 | 2014 |
| Low rank priors for color image regularization T Möllenhoff, E Strekalovskiy, M Möller, D Cremers Energy Minimization Methods in Computer Vision and Pattern Recognition: 10th …, 2015 | 28 | 2015 |
| Proportion priors for image sequence segmentation C Nieuwenhuis, E Strekalovskiy, D Cremers International Conference on Computer Vision (ICCV), 2013 | 18 | 2013 |
| Nonmetric priors for continuous multilabel optimization E Strekalovskiy, C Nieuwenhuis, D Cremers European Conference on Computer Vision (ECCV), 2012 | 17 | 2012 |
| Lifting methods for manifold-valued variational problems T Vogt, E Strekalovskiy, D Cremers, J Lellmann Handbook of Variational Methods for Nonlinear Geometric Data, 95-119, 2020 | 16 | 2020 |
| A co-occurrence prior for continuous multi-Label optimization M Souiai, E Strekalovskiy, C Nieuwenhuis, D Cremers Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR), 2013 | 7 | 2013 |
| Convex Optimization for Scene Understanding M Souiai, C Nieuwenhuis, E Strekalovskiy, D Cremers ICCV Workshop on Graphical Models for Scene Understanding, 2013 | 5 | 2013 |
| Convex relaxation of variational models with applications in image analysis E Strekalovskiy Technische Universität München, 2015 | 2 | 2015 |
| A First Order Primal-dual Algorithm for Nonconvex TVq [TVhochq] Regularization T Möllenhoff, E Strekalovskiy, D Cremers TUM Technische Universität München, Institut für Informatik, 2014 | | 2014 |
| A First Order Primal-Dual Algorithm for Nonconvex TV^q Regularization T Möllenhoff, E Strekalovskiy, D Cremers Technical Report - Technical University Munich, 2014 | | 2014 |
Daniel CremersTechnical University of MunichVerified email at tum.de
