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Conference Paper
M. Schiegg, Heuer, B., Haubold, C., Wolf, S., Köthe, U., and Hamprecht, F. A., “Proof-reading Guidance in Cell Tracking by Sampling from Tracking-by-assignment Models”, in ISBI. Proceedings, 2015, pp. 394-398.PDF icon Technical Report (648.55 KB)
C. Rother, Carlsson, S., and Tell, D., “Projective factorization of planes and cameras in multiple views”, in Proceedings - International Conference on Pattern Recognition, 2002, vol. 16, pp. 737–740.
F. E Sanmartin, Damrich, S., and Hamprecht, F. A., “Probabilistic Watershed: Sampling all spanning forests for seeded segmentation and semi-supervised learning”, in Advances in Neural Information Processing Systems, 2019.
C. Schellewald and Schnörr, C., “Probabilistic Subgraph Matching Based on Convex Relaxation”, in Proc. Int. Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'05), 2005, vol. 3757, pp. 171-186.
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.PDF icon Technical Report (2.95 MB)
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.PDF icon Technical Report (8.18 MB)
J. Hendrik Kappes, Swoboda, P., Savchynskyy, B., Hazan, T., and Schnörr, C., “Probabilistic correlation clustering and image partitioning using perturbed Multicuts”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, vol. 9087, pp. 231–242.
J. Kappes, Swoboda, P., Savchynskyy, B., Hazan, T., and Schnörr, C., “Probabilistic Correlation Clustering and Image Partitioning Using Perturbed Multicuts”, in Proc. SSVM, 2015.
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.PDF icon Technical Report (1.1 MB)
M. Detert, Jirka, G. H., Jehle, M., Klar, M., Jähne, B., Köhler, H. - J., and Wenka, T., “Pressure fluctuations within subsurface gravel bed caused by turbulent open-channel flow”, in Proc. of River Flow 2004, 2004, pp. 695-701.
C. Kondermann, Kondermann, D., and Garbe, C. S., “Postprocessing of optical flows via surface measures and motion inpainting”, in Pattern Recognition, 2008, vol. 5096, p. 355--364.
A. Krull, Brachmann, E., Nowozin, S., Michel, F., Shotton, J., and Rother, C., “PoseAgent: Budget-constrained 6D object pose estimation via reinforcement learning”, in Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, 2017, vol. 2017-Janua, pp. 2566–2574.
F. Michel, Krull, A., Brachmann, E., Yang, M. Ying, Gumhold, S., and Rother, C., “Pose Estimation of Kinematic Chain Instances via Object Coordinate Regression”, 2015, pp. 181.1–181.11.
B. Jähne, “Plenoptic image acquisition and processing”, in Proc.\ Int. Symp. Microoptical Imaging and Projection (MIPS2012), 2012, p. 87--89.
H. Meine, Köthe, U., and Stelldinger, P., “Pixel Approximation Errors in Common Watershed Algorithms”, in Discrete Geometry for Computer Imagery, 2009, vol. 5810, pp. 193-202.PDF icon Technical Report (6.5 MB)
H. Meine, Köthe, U., and Stelldinger, P., “Pixel Approximation Errors in Common Watershed Algorithms”, in Discrete Geometry for Computer Imagery, 2009, vol. 5810, pp. 193-202.
H. Haußecker, Schimpf, U., Garbe, C. S., and Jähne, B., “Physics from IR image sequences: Quantitative analysis of transport models and parameters of air-sea gas transfer”, in Gas Transfer at Water Surfaces, 2002, vol. 127, p. 103--108.
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)
A. Vlasenko and Schnörr, C., “Physically Consistent Variational Denoising of Image Fluid Flow Estimates”, in Pattern Recognition – 30th DAGM Symposium, 2008, vol. 5096, pp. 406–415.
M. Schmidt and Jähne, B., “A physical model of Time-of-Flight 3D imaging systems, including suppression of ambient light”, in 3rd Workshop on Dynamic 3-D Imaging, 2009, vol. 5742, p. 1--15.
J. François Lalonde, Hoiem, D., Efros, A. A., Rother, C., Winn, J., and Criminisi, A., “Photo clip art”, in Proceedings of the ACM SIGGRAPH Conference on Computer Graphics, 2007.
P. Swoboda, Savchynskyy, B., Kappes, J. H., and Schnörr, C., “Persistency by Pruning for General Graphical Models”, in submitted to NIPS 2013., 2013.
B. Antic and Ommer, B., “Per-Sample Kernel Adaptation for Visual Recognition and Grouping”, in Proceedings of the IEEE International Conference on Computer Vision, 2015.PDF icon Technical Report (1.58 MB)
J. Mund, Zouhar, A., Meyer, L., Fricke, H., and Rother, C., “Performance evaluation of LiDAR point clouds towards automated FOD detection on airport aprons”, in Proceedings of ATACCS 2015 - 5th International Conference on Application and Theory of Automation in Command and Control Systems, 2015, pp. 85–94.
J. Mund, Zouhar, A., Meyer, L., Fricke, H., and Rother, C., “Performance evaluation of LiDAR point clouds towards automated FOD detection on airport aprons”, in Proceedings of ATACCS 2015 - 5th International Conference on Application and Theory of Automation in Command and Control Systems, 2015, pp. 85–94.
B. Jähne and Förstner, W., “Performance characteristics of low-level motion estimators in spatiotemporal images”, in DAGM-Workshop Performance Characteristics and Quality of Computer Vision Algorithms, Braunschweig, September 18, 1997, 1997.
D. Kondermann, Abraham, S., Förstner, W., Gehrig, S., Imiya, A., Jähne, B., Klose, F., Magor, M., Mayer, H., Mester, R., Pajdla, T., Reulke, R., and Zimmer, H., “On Performance Analysis of Optical Flow Algorithms”, in Outdoor and Large-Scale Real-Worls Scene Analysis, Dagstuhl-Workshop 2011, 2012, vol. LNCS, pp. 329-355.
C. Rhemann, Rother, C., Wang, J., Gelautz, M., Kohli, P., and Rott, P., “A perceptually motivated online benchmark for image matting”, in 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009, 2009, vol. 2009 IEEE, pp. 1826–1833.
C. Rhemann, Rother, C., Wang, J., Gelautz, M., Kohli, P., and Rott, P., “A perceptually motivated online benchmark for image matting”, in 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009, 2009, vol. 2009 IEEE, pp. 1826–1833.
C. Rhemann, Rother, C., Wang, J., Gelautz, M., Kohli, P., and Rott, P., “A perceptually motivated online benchmark for image matting”, in 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009, 2009, vol. 2009 IEEE, pp. 1826–1833.
M. Bleyer, Rhemann, C., and Rother, C., “PatchMatch Stereo - Stereo Matching with Slanted Support Windows”, 2011, pp. 14.1–14.11.
C. Kräuter, Richter, K. E., Mesarchaki, E., Rocholz, R., Williams, J., and Jähne, B., “Partitioning of the Trasfer Resistance between Air and Water”, in SOLAS Open Science Conference, Washington State, USA, 2012.
F. Hering, Merle, M., Wierzimok, D., and Jähne, B., “Particle tracking in space time sequences”, in Computer Analysis of Images and Patterns, 1995, vol. 970, p. 294--301.
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)

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