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Lenzen, F, Becker, F, Lellmann, J, Petra, S and Schnörr, C (2011). 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

S

Lenzen, F, Lellmann, J, Becker, F and Schnörr, C (2014). Solving QVIs for Image Restoration with Adaptive Constraint Sets. SIAM Journal on Imaging Sciences (SIIMS), in press

Lenzen, F, Lellmann, J, Becker, F and Schnörr, C (2014). Solving Quasi-Variational Inequalities for Image Restoration with Adaptive Constraint Sets. SIAM J. Imag. Sci. 7 2139–2174

Lenzen, F, Lellmann, J, Becker, F and Schnörr, C (2014). Solving Quasi-Variational Inequalities for Image Restoration with Adaptive Constraint Sets. SIAM J.~Imag.~Sci. 7 2139--2174

Technical Report (802.13 KB)

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Lellmann, J and Schnörr, C (2011). Regularizers for Vector-Valued Data and Labeling Problems in Image Processing. Control Systems and Computers. 2 43–54

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Lellmann, J, Lenzen, F and Schnörr, C (2010). Optimality Bounds for Variational Relaxations of Optimal Partition Problems

Lellmann, J, Lenzen, F and Schnörr, C (2011). Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem. Energy Min. Meth. Comp. Vis. Patt. Recogn. Springer. 132-146

F

Lellmann, J, Breitenreicher, D and Schnörr, C (2010). Fast and Exact Primal-Dual Iterations for Variational Problems in Computer Vision. European Conference on Computer Vision (ECCV). Springer Berlin / Heidelberg. 6312 494–505

Lellmann, J, Breitenreicher, D and Schnörr, C (2010). 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)

D

Lellmann, J, Lellmann, B, Widmann, F and Schnörr, C (2013). Discrete and Continuous Models for Partitioning Problems. Int.~J.~Comp.~Visionz. 104 241-269

Technical Report (4.74 MB)

C

Lellmann, J, Becker, F and Schnörr, C (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)

Lellmann, J, Becker, F and Schnörr, C (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

Lellmann, J, Kappes, J H, Yuan, J, Becker, F and Schnörr, C (2009). 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)

Lellmann, J, Kappes, J H, Yuan, J, Becker, F and Schnörr, C (2008). 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)

Lellmann, J, Kappes, J H, Yuan, J, Becker, F, Schnörr, C, Mórken, K and Lysaker, M (2009). Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation. Scale Space and Variational Methods in Computer Vision (SSVM 2009). Springer. 5567 150-162

Lellmann, J and Schnörr, C (2011). Continuous Multiclass Labeling Approaches and Algorithms. SIAM J.~Imag.~Sci. 4 1049-1096

Technical Report (4.31 MB)

Lellmann, J and Schnörr, C (2011). Continuous Multiclass Labeling Approaches and Algorithms. CoRR. abs/1102.5448. http://arxiv.org/abs/1102.5448

Lellmann, J and Schnörr, C (2010). Continuous Multiclass Labeling Approaches And Algorithms. Univ. of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/10460/

Kappes, J H, Andres, B, Hamprecht, F A, Schnörr, C, Nowozin, S, Batra, D, Kim, S, Kausler, B X, Kröger, T, Lellmann, J, Komodakis, N, Savchynskyy, B and Rother, C (2015). A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. Int.~J.~Comp.~Vision

Technical Report (5.12 MB)

Kappes, J H, Andres, B, Hamprecht, F A, Schnörr, C, Nowozin, S, Batra, D, Kim, S, Kausler, B X, Kröger, T, Lellmann, J, Komodakis, N, Savchynskyy, B and Rother, C (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)

Kappes, J H, Andres, B, Hamprecht, F A, Schnörr, C, Nowozin, S, Batra, D, Kim, S, Kausler, B X, Kröger, T, Lellmann, J, Komodakis, N, Savchynskyy, B and Rother, C (2014). A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. CoRR. http://arxiv.org/abs/1404.0533

Kappes, J H, Andres, B, Hamprecht, F A, Schnörr, C, Nowozin, S, Batra, D, Sungwoong, K, Kausler, B X, Lellmann, J, Komodakis, N and Rother, C (2013). A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems. CVPR 2013. Proceedings

Technical Report (1.35 MB)

Lenzen, F, Becker, F, Lellmann, J, Petra, S and Schnörr, C (2013). A Class of Quasi-Variational Inequalities for Adaptive Image Denoising and Decomposition. Computational Optimization and Applications (COAP). 54 (2) 371-398

A

Lenzen, F, Becker, F and Lellmann, J (2013). 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