HCI Logo
Heidelberg University Logo
IWR Logo

Publications

Export 18 results:
Author Title Type [ Year(Desc)]
Filters: Author is Lellmann, Jan  [Clear All Filters]
2011
Lellmann, J, Lenzen, F and Schnörr, C (2011). Optimality Bounds For A Variational Relaxation Of The Image Partitioning Problem. IPA group, Heidelberg University. http://arxiv.org/abs/1112.0974
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. 6819 132--146PDF icon Technical Report (1 MB)
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. 6819 132–146
Breitenreicher, D, Lellmann, J and Schnörr, C (2011). Sparse Template-Based Variational Image Segmentation. Advances in Adaptive Data Analysis. 3 149-166PDF icon Technical Report (866.28 KB)
Breitenreicher, D, Lellmann, J and Schnörr, C (2011). Sparse Template-Based Variational Image Segmentation. Advances in Adaptive Data Analysis. 3 149-166
2012
Lellmann, J, Lenzen, F and Schnörr, C (2012). Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem. Journal of Mathematical Imaging and Vision. Springer. 47 239-257
Lellmann, J, Lenzen, F and Schnörr, C (2012). Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem. Journal of Mathematical Imaging and Vision. Springer. 47 239-257PDF icon Technical Report (616.16 KB)
Lenzen, F, Becker, F, Lellmann, J, Petra, S and Schnörr, C (2012). Variational Image Denoising with Adaptive Constraint Sets. Proceedings of the 3rd International Conference on Scale Space and Variational Methods in Computer Vision 2011. Springer. 206-217
Lenzen, F, Becker, F, Lellmann, J, Petra, S and Schnörr, C (2012). Variational Image Denoising with Adaptive Constraint Sets. LNCS. Springer. 206-217PDF icon Technical Report (649.03 KB)
2013
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) 2013. Springer. 54 371--398PDF icon Technical Report (702.08 KB)
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. Springer Netherlands. 54 371-398. http://dx.doi.org/10.1007/s10589-012-9456-0PDF icon Technical Report (748.66 KB)
Breitenreicher, D, Lellmann, J and Schnörr, C (2013). COAL: a generic modelling and prototyping framework for convex optimization problems of variational image analysis. Optimization Methods and Software. 28 1081-1094. http://www.tandfonline.com/doi/abs/10.1080/10556788.2012.672571PDF icon Technical Report (1.69 MB)
Kappes, J H, Andres, B, Hamprecht, F A, Schnörr, C, Nowozin, S, Batra, D, Kim, S, Kausler, B X, Lellmann, J, Komodakis, N and Rother, C (2013). A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problem. CVPRPDF icon Technical Report (1.35 MB)
Lellmann, J, Lenzen, F and Schnörr, C (2013). Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem. Journal of Mathematical Imaging and Vision. 47 (3) 239-257
2014
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. abs/1404.0533. http://hci.iwr.uni-heidelberg.de/opengm2/PDF icon Technical Report (3.32 MB)
2015
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. 115 155–184
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. 115 155–184
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. 115 155–184. http://hci.iwr.uni-heidelberg.de/opengm2/