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V

F. Becker, Lenzen, F., Kappes, J. H., and Schnörr, C., “Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences”, International Journal of Computer Vision, vol. 105, no. 3, p. 269--297, 2013.

Technical Report (15.4 MB)

F. Becker, Lenzen, F., Kappes, J. H., and Schnörr, C., “Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences”, in 2011 IEEE International Conference on Computer Vision (ICCV), 2011, p. 1692 -- 1699.

Technical Report (4.9 MB)

F. Becker, Lenzen, F., Kappes, J. H., and Schnörr, C., “Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences”, in 2011 IEEE International Conference on Computer Vision ICCV, 2011, pp. 1692-1699.

F. Becker, Lenzen, F., Kappes, J. H., and Schnörr, C., “Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences”, International Journal of Computer Vision, vol. 105 (3), pp. 269-297, 2013.

S

M. Bergtholdt, Kappes, J. H., Schmidt, S., and Schnörr, C., “A Study of Parts-Based Object Class Detection Using Complete Graphs”, Int.~J.~Comp.~Vision, vol. 87, pp. 93-117, 2010.

Technical Report (2.18 MB)

B. Savchynskyy, Kappes, J. H., Schmidt, S., and Schnörr, C., “A Study of Nesterov's Scheme for Lagrangian Decomposition and MAP Labeling”, in IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2011.

Technical Report (408.99 KB)

B. Savchynskyy, Kappes, J. H., Schmidt, S., and Schnörr, C., “A Study of Nesterov's Scheme for Lagrangian Decomposition and MAP Labeling”, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), accepted as oral presentation, pp. 1817 - 1823, 2011.

S. Schmidt, Kappes, J. H., Bergtholdt, M., Pekar, V., Dries, S., Bystrov, D., and Schnörr, C., “Spine Detection and Labeling Using a Parts-Based Graphical Model”, in Proc. 20th International Conference on Information Processing in Medical Imaging (IPMI 2007), 2007, vol. 4584, pp. 122-133.

Technical Report (1.46 MB)

P

B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., “Probabilistic Image Segmentation with Closedness Constraints”, in ICCV, Proceedings, 2011, pp. 2611 - 2618.

Technical Report (8.18 MB)

B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., “Probabilistic Image Segmentation with Closedness Constraints”, in Proceedings of ICCV, 2011.

B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., “Probabilistic Image Segmentation with Closedness Constraints”, in Proceedings of ICCV, 2011.

Technical Report (2.95 MB)

J. H. Kappes, Swoboda, P., Savchynskyy, B., Hazan, T., and Schnörr, C., “Probabilistic Correlation Clustering and Image Partitioning Using Perturbed Multicuts”, in Proc.~SSVM, 2015.

Technical Report (1.1 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 Scale Space and Variational Methods (SSVM 2013), 2013.

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.

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 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 by Pruning for MAP-inference with General GraphicalModels”, CVPR. Proceedings. pp. 1170-1177, 2014.

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.

Technical Report (703.34 KB)

M

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.

Technical Report (1.49 MB)

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, 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.

Technical Report (557.49 KB)

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.

Technical Report (1.91 MB)

L

B. Andres, Kappes, J. H., Köthe, U., and Hamprecht, F. A., “The Lazy Flipper: MAP Inference in Higher-Order Graphical Models by Depth-limited Exhaustive Search”, ArXiv e-prints, 2010.

Technical Report (625.06 KB)

B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., “The Lazy Flipper: Efficient Depth-limited Exhaustive Search in Discrete Graphical Models”, in ECCV 2012, 2012.

Technical Report (532.64 KB)

B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., “The Lazy Flipper: Efficient Depth-Limited Exhaustive Search in Discrete Graphical Models”, in Computer Vision - {ECCV} 2012 - 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Proceedings, Part {VII}, 2012.

Technical Report (446.28 KB)

H

J. H. Kappes, Speth, M., Reinelt, G., and Schnörr, C., “Higher-order Segmentation via Multicuts”, ArXiv e-prints. 2013.

Technical Report (1.07 MB)

G

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.

Technical Report (491.56 KB)

J. H. Kappes, Speth, M., Andres, B., Reinelt, G., and Schnörr, C., “Globally Optimal Image Partitioning by Multicuts”, in EMMCVPR, 2011, pp. 31-44.

Technical Report (7.3 MB)

J. H. Kappes, Speth, M., Andres, B., Reinelt, G., and Schnörr, C., “Globally Optimal Image Partitioning by Multicuts”, in EMMCVPR, 2011.

Technical Report (7.47 MB)

B. Savchynskyy, Kappes, J. H., Swoboda, P., and Schnörr, C., “Global MAP-Optimality by Shrinking the Combinatorial Search Area with Convex Relaxation”, in NIPS. Proceedings, 2013, pp. 1950-1958.

B. Savchynskyy, Kappes, J. H., Swoboda, P., and Schnörr, C., “Global MAP-Optimality by Shrinking the Combinatorial Search Area with Convex Relaxation”, in NIPS, 2013.

Technical Report (499.17 KB)

F

T. Beier, Hamprecht, F. A., and Kappes, J. H., “Fusion Moves for Correlation Clustering”, in CVPR. Proceedings, 2015, pp. 3507-3516.

Technical Report (1.19 MB)

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