Publications
Adaptive Second-Order Total Variation: An Approach Aware of Slope
Discontinuities. Proceedings of the 4th International Conference on Scale Space and
Variational Methods in Computer Vision SSVM. Springer. 7893 61-73
(2013). A Class of Quasi-Variational Inequalities for Adaptive Image Denoising
and Decomposition. Computational Optimization and Applications (COAP). 54 (2) 371-398
(2013). A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems. CVPR 2013. Proceedings
Technical Report (1.35 MB)
(2013). 
A Comparative Study of Modern Inference Techniques for Structured
Discrete Energy Minimization Problems. CoRR. http://arxiv.org/abs/1404.0533
(2014). A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. Int.~J.~Comp.~Vision
Technical Report (5.12 MB)
(2015). 
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. International Journal of Computer Vision. 1-30
Technical Report (1.5 MB)
(2015). 
Continuous Multiclass Labeling Approaches and Algorithms. CoRR. abs/1102.5448. http://arxiv.org/abs/1102.5448
(2011). Continuous Multiclass Labeling Approaches and Algorithms. SIAM J.~Imag.~Sci. 4 1049-1096
Technical Report (4.31 MB)
(2011). 
Continuous Multiclass Labeling Approaches And Algorithms. Univ. of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/10460/
(2010). Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation. Scale Space and Variational Methods in Computer Vision (SSVM 2009). Springer. 5567 150-162
Technical Report (1.75 MB)
(2009). 
Convex Multi-Class Image Labeling By Simplex-Constrained Total Variation. IWR, University of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/8759/
Technical Report (2.6 MB)
(2008). 
Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation. Scale Space and Variational Methods in Computer Vision (SSVM 2009). Springer. 5567 150-162
(2009). Convex Optimization for Multi-Class Image Labeling with a Novel Family
of Total Variation Based Regularizers. Proceedings of the IEEE Conference on Computer Vision (ICCV 09) Kyoto, Japan. 646-653
(2009). Convex Optimization for Multi-Class Image Labeling with a Novel Family of Total Variation Based Regularizers. IEEE International Conference on Computer Vision (ICCV). 646 -- 653
Technical Report (930.18 KB)
(2009). 
Discrete and Continuous Models for Partitioning Problems. Int.~J.~Comp.~Visionz. 104 241-269
Technical Report (4.74 MB)
(2013). 
Fast and Exact Primal-Dual Iterations for Variational Problems in Computer Vision. European Conference on Computer Vision (ECCV). Springer Berlin / Heidelberg. 6312 494--505
Technical Report (1.94 MB)
(2010). 
Optimality Bounds for a Variational Relaxation of the Image Partitioning
Problem. Energy Min. Meth. Comp. Vis. Patt. Recogn. Springer. 132-146
(2011). (2010). Regularizers for Vector-Valued Data and Labeling Problems in Image Processing. Control Systems and Computers. 2 43--54
(2011). Solving Quasi-Variational Inequalities for Image Restoration with Adaptive Constraint Sets. SIAM J.~Imag.~Sci. 7 2139--2174
Technical Report (802.13 KB)
(2014). 
Solving QVIs for Image Restoration with Adaptive Constraint Sets. SIAM Journal on Imaging Sciences (SIIMS), in press
(2014). Variational Image Denoising with Adaptive Constraint Sets. Proceedings of the 3nd International Conference on Scale Space and
Variational Methods in Computer Vision 2011, in press. Springer. 6667 206-217
(2011).