Publications

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Cremers, D, Sochen, N and Schnörr, C (2004). Multiphase Dynamic Labeling for Variational Recognition-Driven Image Segmentation. Computer Vision – ECCV 2004. Springer. 3024 74-86
Cremers, D, Sochen, N and Schnörr, C (2006). Multiphase Dynamic Labeling for Variational Recognition-Driven Image Segmentation. ijcv. 66 67-81
Bruhn, A, Weickert, J, Kohlberger, T and Schnörr, C (2006). A Multigrid Platform for Real-Time Motion Computation with Discontinuity-Preserving Variational Methods. Int.~J.~Computer Vision. 70 257-277PDF icon Technical Report (447.65 KB)
Bruhn, A, Weickert, J, Kohlberger, T and Schnörr, C (2006). A Multigrid Platform for Real-Time Motion Computation with Discontinuity-Preserving Variational Methods. Int. J. Computer Vision. 70 257-277
Kappes, J Hendrik, Swoboda, P, Savchynskyy, B, Hazan, T and Schnörr, C (2016). Multicuts and Perturb & MAP for Probabilistic Graph Clustering. Journal of Mathematical Imaging and Vision. 56 221–237. http://arxiv.org/abs/1601.02088
Kappes, J H, Schmidt, S and Schnörr, C (2010). MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation. European Conference on Computer Vision (ECCV). Springer. 6313 735--747
Kappes, J H, Schmidt, S and Schnörr, C (2010). MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation. European Conference on Computer Vision (ECCV). Springer Berlin / Heidelberg. 6313 735--747PDF icon Technical Report (1.49 MB)
Cremers, D and Schnörr, C (2002). Motion Competition: Variational Integration of Motion Segmentation and Shape Regularization. Pattern Recognition, Proc. 24th DAGM Symposium. Springer, Zürich, Switzerland. 2449 472–480
Schmitzer, B and Schnörr, C (2013). Modelling convex shape priors and matching based on the Gromov-Wasserstein distance. Journal of Mathematical Imaging and Vision. 46 143-159PDF icon Technical Report (957.78 KB)
Schmitzer, B and Schnörr, C (2013). Modelling convex shape priors and matching based on the Gromov-Wasserstein distance. Journal of Mathematical Imaging and Vision. 46 143-159
Breitenreicher, D and Schnörr, C (2011). Model-Based Multiple Rigid Object Detection and Registration in Unstructured Range Data. Int.~J.~Comp.~Vision. 92 32--52. http://www.springerlink.com/content/v266873267180602/PDF icon Technical Report (4.3 MB)
Breitenreicher, D and Schnörr, C (2011). Model-Based Multiple Rigid Object Detection and Registration in Unstructured Range Data. Int. J. Comp. Vision. 92 32–52. http://www.springerlink.com/content/v266873267180602/
Welk, M, Weickert, J, Becker, F, Schnörr, C, Feddern, C and Burgeth, B (2007). Median and related local filters for tensor-valued images. Signal Processing. 87 291-308PDF icon Technical Report (1007.29 KB)
Welk, M, Becker, F, Schnörr, C and Weickert, J (2005). Matrix-Valued Filters as Convex Programs. Scale-Space 2005. Springer. 3459 204–216
Kappes, J H, Beier, T and Schnörr, C (2014). MAP-Inference on Large Scale Higher-Order Discrete Graphical Models by Fusion Moves. Computer Vision - {ECCV} 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part {II}. http://dx.doi.org/10.1007/978-3-319-16181-5_37PDF icon Technical Report (557.49 KB)
Kappes, J Hendrik, Beier, T and Schnörr, C (2014). MAP-Inference on Large Scale Higher-Order Discrete Graphical Models by Fusion Moves. International Workshop on Graphical Models in Computer Vision
Kappes, J H and Schnörr, C (2008). MAP-Inference for Highly-Connected Graphs with DC-Programming. Pattern Recognition -- 30th DAGM Symposium. Springer Verlag. 5096 1--10PDF icon Technical Report (1.91 MB)

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