Publications

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Besse, F, Rother, C, Fitzgibbon, A and Kautz, J (2014). PMBP: PatchMatch Belief Propagation for correspondence field estimation. International Journal of Computer Vision. 110 2–13
Geiler, T (2008). Polarisationsbildgebung in der industriellen Qualitätskontrolle. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/8533
Michel, F, Krull, A, Brachmann, E, Yang, M Ying, Gumhold, S and Rother, C (2015). Pose Estimation of Kinematic Chain Instances via Object Coordinate Regression. 181.1–181.11
Krull, A, Brachmann, E, Nowozin, S, Michel, F, Shotton, J and Rother, C (2017). PoseAgent: Budget-constrained 6D object pose estimation via reinforcement learning. Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017. 2017-Janua 2566–2574. http://arxiv.org/abs/1612.03779
Kondermann, C (2009). Postprocessing and Restoration of Optical Flows. IWR, Fakultät für Mathematik und Informatik, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/9681
Kondermann, C (2009). Postprocessing and Restoration of Optical Flows. IWR, Fakultät für Mathematik und Informatik, Univ. Heidelberg
Kondermann, C, Kondermann, D and Garbe, C S (2008). Postprocessing of optical flows via surface measures and motion inpainting. Pattern Recognition. 5096 355--364
Jähne, (2004). Practical Handbook On Image Processing For Scientific And Technical Applications, 2nd ed. CRC Press
Jähne, (1997). Practical Handbook On Image Processing For Scientific Applications. CRC-Press, Boca Raton, FL, USA
Hamprecht, F A, Jost, D, Rüttimann, M, Calamai, F and Kowalski, J J (2001). Preliminary results on the prediction of countershock success with fibrillation power. Resuscitation. 50 297-299
Detert, M, Jirka, G H, Jehle, M, Klar, M, Jähne, B, Köhler, H - J and Wenka, T (2004). Pressure fluctuations within subsurface gravel bed caused by turbulent open-channel flow. Proc. of River Flow 2004. A. A. Balkema Publishers. 695-701
Haller, S, Prakash, M, Hutschenreiter, L, Pietzsch, T, Rother, C, Jug, F, Swoboda, P and Savchynskyy, B (2020). A Primal-Dual Solver for Large-Scale Tracking-by-Assignment. AISTATS 2020PDF icon PDF (1.04 MB)
Jäger, M and Hamprecht, F A (2008). Principal Component Imagery for the Quality Monitoring of Dynamic Laser Welding Processes. IEEE Transactions on Industrial Electronics. 56:4 1307-1313
Jähne, B, Scharr, H, Körkel, S, Jähne, B, Haußecker, H and Geißler, P (1999). Principles of Filter Design. Handbook of Computer Vision and Applications. Academic Press. 2 125--151
Jähne, (2008). Prinzipien und Verfahren zur Aufnahme spektraler Bilddaten - Vereinfachte Bildanalyse. QZ. 53 45--48
Weber, S, Schüle, T and Schnörr, C (2005). Prior Learning and Convex-Concave Regularization of Binary Tomography. Electr. Notes in Discr. Math. 20 313-327
Geese, M, Ruhnau, P and Jähne, B (2013). PRNU and DSNU Maximum Likelihood Estimation Using Sensor Statistics. tm --- Technisches Messen. 80 321--328
Hehn, T (2017). A Probabilistic Approach To Learn Complex Differentiable Split Functions In Decision Trees Using Gradient Ascent. Heidelberg University
Kappes, J H, Swoboda, P, Savchynskyy, B, Hazan, T and Schnörr, C (2015). Probabilistic Correlation Clustering and Image Partitioning Using Perturbed Multicuts. Proc.~SSVM. SpringerPDF icon Technical Report (1.1 MB)
Kappes, J Hendrik, Swoboda, P, Savchynskyy, B, Hazan, T and Schnörr, C (2015). Probabilistic correlation clustering and image partitioning using perturbed Multicuts. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 9087 231–242
Kappes, J, Swoboda, P, Savchynskyy, B, Hazan, T and Schnörr, C (2015). Probabilistic Correlation Clustering and Image Partitioning Using Perturbed Multicuts. Proc. SSVM. Springer
Kolmogorov, V, Criminisi, A, Blake, A, Cross, G and Rother, C (2006). Probabilistic fusion of stereo with color and contrast for bilayer segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence. 28 1480–1492. http://research.microsoft.com/vision/cambridge
Rathke, F (2015). Probabilistic Graphical Models for Medical Image Segmentation. University Heidelberg
Andres, B, Kappes, J H, Beier, T, Köthe, U and Hamprecht, F A (2011). Probabilistic Image Segmentation with Closedness Constraints. Proceedings of ICCVPDF icon Technical Report (2.95 MB)
Andres, B, Kappes, J H, Beier, T, Köthe, U and Hamprecht, F A (2011). Probabilistic Image Segmentation with Closedness Constraints. Proceedings of ICCV
Andres, B, Kappes, J H, Beier, T, Köthe, U and Hamprecht, F A (2011). Probabilistic Image Segmentation with Closedness Constraints. ICCV, Proceedings. 2611 - 2618PDF icon Technical Report (8.18 MB)
Rathke, F, Schmidt, S and Schnörr, C (2014). Probabilistic Intra-Retinal Layer Segmentation in 3-D OCT Images Using Global Shape Regularization. Med. Image Anal. 18 781–794
Rathke, F, Schmidt, S and Schnörr, C (2014). Probabilistic Intra-Retinal Layer Segmentation in 3-D OCT Images Using Global Shape Regularization. Medical Image Analysis. 18 781-794PDF icon Technical Report (4.07 MB)
Rathke, F, Schmidt, S and Schnörr, C (2014). Probabilistic Intra-Retinal Layer Segmentation in 3-D OCT Images Using Global Shape Regularization. Medical Image Analysis. 18 781-794
Schellewald, C and Schnörr, C (2005). Probabilistic Subgraph Matching Based on Convex Relaxation. Proc. Int. Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'05). Springer. 3757 171-186
Chellappa, R and Machinery., Afor Comput (2010). Proceedings - 7th Indian Conference on Computer Vision, Graphics and Image Processing, ICVGIP 2010. ACM International Conference Proceeding Series. ACM
Trittler, S (2007). Processing of Interferometric Data. University of Heidelberg
Görlitz, L, Menze, B H, Kelm, B Michael and Hamprecht, F A (2009). Processing Spectral Data. Surface and Interface Analysis. 41 636-644PDF icon Technical Report (4.17 MB)
Rother, C, Carlsson, S and Tell, D (2002). Projective factorization of planes and cameras in multiple views. Proceedings - International Conference on Pattern Recognition. 16 737–740
Distributions, L (2014). Proof of Lemma 2 Proof of Lemma 3 Proof of Theorem 4 Proof of Lemma 10. Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics. 9–11

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