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Publications

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Conference Paper
A. Vlasenko and Schnörr, C., “Physically Consistent Variational Denoising of Image Fluid Flow Estimates”, in Pattern Recognition -- 30th DAGM Symposium, 2008, vol. 5096, p. 406--415.PDF icon Technical Report (1.6 MB)
P. Swoboda, Savchynskyy, B., Kappes, J. H., and Schnörr, C., “Persistency by Pruning for General Graphical Models”, in submitted to NIPS 2013., 2013.
P. Swoboda, Savchynskyy, B., Kappes, J. H., and Schnörr, C., “Partial Optimality via Iterative Pruning for the Potts Model”, in Proceedings of the 4th International Conference on Scale Space and Variational Methods in Computer Vision SSVM, 2013, pp. 477-488.
P. Swoboda, Savchynskyy, B., Kappes, J. H., and Schnörr, C., “Partial Optimality via Iterative Pruning for the Potts Model”, in Scale Space and Variational Methods (SSVM 2013), 2013.PDF icon Technical Report (159.71 KB)
P. Swoboda, Savchynskyy, B., Kappes, J. H., and Schnörr, C., “Partial Optimality via Iterative Pruning for the Potts Model”, in Scale Space and Variational Methods (SSVM 2013), 2013.
P. Swoboda, Savchynskyy, B., Kappes, J. H., and Schnörr, C., “Partial Optimality by Pruning for MAP-inference with General Graphical Models”, in IEEE Conference on Computer Vision and Pattern Recognition 2014, 2014.PDF icon Technical Report (703.34 KB)
P. Swoboda, Savchynskyy, B., Kappes, J. H., and Schnörr, C., “Partial Optimality by Pruning for MAP-inference with General Graphical Models”, in IEEE Conference on Computer Vision and Pattern Recognition 2014, 2014.
F. Rathke, Schmidt, S., and Schnörr, C., “Order Preserving and Shape Prior Constrained Intra-Retinal Layer Segmentation in Optical Coherence Tomography”, in MICCAI 2011, Proceedings, 2011, vol. 6893, pp. 370-377.
F. Rathke, Schmidt, S., and Schnörr, C., “Order Preserving and Shape Prior Constrained Intra-Retinal Layer Segmentation in Optical Coherence Tomography”, in MICCAI, 2011, vol. 6893, p. 370--377.PDF icon Technical Report (1.12 MB)
F. Rathke, Schmidt, S., and Schnörr, C., “Order Preserving and Shape Prior Constrained Intra-Retinal Layer Segmentation in Optical Coherence Tomography”, in MICCAI, 2011, vol. 6893, pp. 370–377.
J. Lellmann, Lenzen, F., and Schnörr, C., “Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem”, in Energy Min. Meth. Comp. Vis. Patt. Recogn., 2011, pp. 132-146.
J. Lellmann, Lenzen, F., and Schnörr, C., “Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem”, in Energy Min. Meth. Comp. Vis. Patt. Recogn., 2011, vol. 6819, p. 132--146.PDF icon Technical Report (1 MB)
J. Lellmann, Lenzen, F., and Schnörr, C., “Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem”, in Energy Min. Meth. Comp. Vis. Patt. Recogn., 2011, vol. 6819, pp. 132–146.
P. Ruhnau, Stahl, A., and Schnörr, C., “On-Line Variational Estimation of Dynamical Fluid Flows with Physics-Based Spatio-Temporal Regularization”, in Proc.~DAGM 2006, 2006, vol. 375-388, pp. 375-388.PDF icon Technical Report (902.47 KB)
B. Schmitzer and Schnörr, C., “Object Segmentation by Shape Matching with Wasserstein Modes”, in Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR 2013), 2013, pp. 123-136.
D. Cremers, Kohlberger, T., and Schnörr, C., “Nonlinear Shape Statistics via Kernel Spaces”, in Mustererkennung 2001, 2001, vol. 2191, p. 269--276.PDF icon Technical Report (324.55 KB)
D. Cremers, Kohlberger, T., and Schnörr, C., “Nonlinear Shape Statistics via Kernel Spaces”, in Mustererkennung 2001, Munich, Germany, 2001, vol. 2191, pp. 269–276.
D. Cremers, Kohlberger, T., and Schnörr, C., “Nonlinear Shape Statistics in Mumford-Shah Based Segmentation”, in Computer Vision -- ECCV 2002), 2002, vol. 2351, p. 93--108.PDF icon Technical Report (636.58 KB)
D. Cremers, Kohlberger, T., and Schnörr, C., “Nonlinear Shape Statistics in Mumford-Shah Based Segmentation”, in Computer Vision – ECCV 2002), 2002, vol. 2351, pp. 93–108.
D. Cremers, Sochen, N., and Schnörr, C., “Multiphase Dynamic Labeling for Variational Recognition-Driven Image Segmentation”, in Computer Vision – ECCV 2004, 2004, vol. 3024, pp. 74-86.
J. H. Kappes, Schmidt, S., and Schnörr, C., “MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation”, in European Conference on Computer Vision (ECCV), 2010, vol. 6313, p. 735--747.
J. H. Kappes, Schmidt, S., and Schnörr, C., “MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation”, in European Conference on Computer Vision (ECCV), 2010, vol. 6313, p. 735--747.PDF icon Technical Report (1.49 MB)
D. Cremers and Schnörr, C., “Motion Competition: Variational Integration of Motion Segmentation and Shape Regularization”, in Pattern Recognition, Proc. 24th DAGM Symposium, Zürich, Switzerland, 2002, vol. 2449, pp. 472–480.
M. Welk, Becker, F., Schnörr, C., and Weickert, J., “Matrix-Valued Filters as Convex Programs”, in Scale-Space 2005, 2005, vol. 3459, pp. 204–216.
J. H. Kappes, Beier, T., and Schnörr, C., “MAP-Inference on Large Scale Higher-Order Discrete Graphical Models by Fusion Moves”, in Computer Vision - {ECCV} 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part {II}, 2014.PDF icon Technical Report (557.49 KB)
J. Hendrik Kappes, Beier, T., and Schnörr, C., “MAP-Inference on Large Scale Higher-Order Discrete Graphical Models by Fusion Moves”, in International Workshop on Graphical Models in Computer Vision, 2014.
J. H. Kappes and Schnörr, C., “MAP-Inference for Highly-Connected Graphs with DC-Programming”, in Pattern Recognition -- 30th DAGM Symposium, 2008, vol. 5096, p. 1--10.PDF icon Technical Report (1.91 MB)
D. Cremers, Schnörr, C., Weickert, J., and Schellewald, C., “Learning Translation Invariant Shape Knowledge for Steering Diffusion-Snakes”, in 3rd Workshop on Dynamic Perception, Berlin, Germany, 2000, vol. 9, pp. 117–122.
M. Bergtholdt, Kappes, J. H., and Schnörr, C., “Learning of Graphical Models and Efficient Inference for Object Class Recognition”, in Proc. DAGM 2006, 2006, vol. 375-388, pp. 375-388.
J. Berger and Schnörr, C., “Joint Recursive Monocular Filtering of Camera Motion and Disparity Map”, in 38th German Conference on Pattern Recognition, Hannover, 2016.PDF icon Technical Report (2.34 MB)
J. Berger and Schnörr, C., “Joint Recursive Monocular Filtering of Camera Motion and Disparity Map”, in 38th German Conference on Pattern Recognition, 2016.
D. Breitenreicher and Schnörr, C., “Intrinsic Second-Order Geometric Optimization for Robust Point Set Registration Without Correspondence”, in Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR 2009), 2009, vol. 5681, pp. 274-287.PDF icon Technical Report (752.29 KB)
D. Breitenreicher and Schnörr, C., “Intrinsic Second-Order Geometric Optimization for Robust Point Set Registration Without Correspondence”, in Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR 2009), 2009, vol. 5681, pp. 274-287.
B. Schmitzer and Schnörr, C., “A Hierarchical Approach to Optimal Transport”, in Scale Space and Variational Methods (SSVM 2013), 2013, pp. 452-464.
R. Karim, Bergtholdt, M., Kappes, J. H., and Schnörr, C., “Greedy-Based Design of Sparse Two-Stage SVMs for Fast Classification”, in Pattern Recognition -- 29th DAGM Symposium, 2007, vol. 4713, pp. 395-404.PDF icon Technical Report (491.56 KB)

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