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Bleyer, M, Rother, C, Kohli, P, Scharstein, D and Sinha, S (2011). Object stereo Joint stereo matching and object segmentation. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 3081–3088
Bleyer, M, Rother, C and Kohli, P (2010). Surface stereo with soft segmentation. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 1570–1577
Blattmann, A, Milbich, T, Dorkenwald, M and Ommer, B (2021). Behavior-Driven Synthesis of Human Dynamics. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). https://arxiv.org/abs/2103.04677
Blake, A, Criminisi, A, Cross, G, Kolmogorov, V and Rother, C (2007). Fusion of stereo, colour and contrast. Springer Tracts in Advanced Robotics. 28. www.research.microsoft.com/vision/cambridge
Bister, D, Rohr, K and Schnörr, C (1990). Automatische Bestimmung der Trajektorien von sich bewegenden Objekten aus einer Grauwertbildfolge. Mustererkennung 1990, 12. DAGM-Symposium. Springer-Verlag, Oberkochen-Aalen. 254 44–51
Biller, A, Badde, S, Nagel, A, Neumann, J O, Wick, W, Hertenstein, A, Bendszus, M, Sahm, F, Benkhedah, N and Kleesiek, J (2016). Improved Brain Tumor Classification by Sodium MR Imaging: Prediction of IDH Mutation Status and Tumor Progression. American Journal of Neuroradiology. 37 66-73
Billen, T (1988). Entwicklung Einer Lda-Miniatursonde Zur Messung Der Strömungsgeschwindigkeit Und Ihrer Fluktuationen In Wasser. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Biesdorf, A, Wörz, S, von Tengg-Kobligk, H, Rohr, K and Schnörr, C (2015). 3D Segmentation of Vessels by Incremental Implicit Polynomial Fitting and Convex Optimization. Proc.~ISBIPDF icon Technical Report (611.33 KB)
Bhowmik, A, Gumhold, S, Rother, C and Brachmann, E (2019). Reinforced Feature Points: Optimizing Feature Detection and Description for a High-Level Task. http://arxiv.org/abs/1912.00623
Bhowmik, A, Gumhold, S, Rother, C and Brachmann, E (2020). Reinforced Feature Points: Optimizing Feature Detection and Description for a High-Level Task. CVPR 2020 (oral). http://arxiv.org/abs/1912.00623PDF icon PDF (2.74 MB)
Beyer, M (1997). Skalenraumanalyse nichtlinearer Wasseroberflächenwellen. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Beyer, M (1993). Untersuchung Der Relaxationszeiten Von Winderzeugten Wasseroberflächenwellen Durch Periodische Variation Der Windgeschwindigkeit. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Beyer, M, Jähne, B and Melville, W K (1994). Laboratory studies of long-wave/short-wave interaction using wavelet analysis of space-time images. Proc. 2nd Inter. Conf. on Air-Sea Interaction and on Meteorology and Oceanography of the Coastal Zone, Lisbon, 22.--27. September 1994
Beushausen, V, Roetmann, K, Schmunk, W, Wellhausen, M, Garbe, C S and Jähne, B (2009). 2D-measurement technique for simultaneous quantitative determination of mixing ratio and velocity field in microfluidic applications. Imaging Measurement Methods for Flow Analysis, Results of the DFG Priority Programme 1147 Imaging Measurement Methods for Flow Analysis 2003-2009. Springer. 106 155--164
Beurer, M (2002). Entwicklung Von Algorithmen Zur Analyse Interferometrischer Aufnahmen. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Besse, F, Rother, C, Fitzgibbon, A and Kautz, J (2014). PMBP: PatchMatch Belief Propagation for correspondence field estimation. International Journal of Computer Vision. Kluwer Academic Publishers. 110 2–13
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
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
Berthe, A, Kondermann, D, Jähne, B and Ketzscher, U (2009). The wall PIV measurement technique for near wall flow fields in biofliud mechanics. Imaging Measurement Methods for Flow Analysis, Results of the DFG Priority Programme 1147 Imaging Measurement Methods for Flow Analysis 2003-2009. Springer. 106 11--20
Berthe, A, Kondermann, D, Christensen, C, Goubergrits, L, Garbe, C S, Affeld, K and Kertzscher, U (2010). Three-dimensional, three-component wall-PIV. Exp. Fluids. 48 online
Beringer, O (1998). Ein Messsystem Zur Untersuchung Von Sedimentverlagerungen Und Durchmischungsprozessen Mittels Digitaler Bildfolgenanalyse. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Bergtholdt, M, Cremers, D and Schnörr, C (2005). Variational Segmentation with Shape Priors. Handbook of Mathematical Models in Computer Vision. Springer. 147-160
Bergtholdt, M, Kappes, J H, Schmidt, S and Schnörr, C (2010). A Study of Parts-Based Object Class Detection Using Complete Graphs. Int. J. Comp. Vision. 87 93-117. http://www.springerlink.com/openurl.asp?genre=article&id=doi:10.1007/s11263-009-0209-1
Bergtholdt, M, Kappes, J H and Schnörr, C (2006). Learning of Graphical Models and Efficient Inference for Object Class Recognition. Proc. DAGM 2006. Springer. 375-388 375-388
Bergtholdt, M and Schnörr, C (2005). Shape Priors and Online Appearance Learning for Variational Segmentation and Object Recognition in Static Scenes. Pattern Recognition, Proc. 27th DAGM Symposium. Springer. 3663 342–350
Bergtholdt, M, Kappes, J H, Schmidt, S and Schnörr, C (2010). A Study of Parts-Based Object Class Detection Using Complete Graphs. Int.~J.~Comp.~Vision. 87 93-117. http://www.springerlink.com/openurl.asp?genre=article&id=doi:10.1007/s11263-009-0209-1PDF icon Technical Report (2.18 MB)
Berger, J and Schnörr, C (2016). Joint Recursive Monocular Filtering of Camera Motion and Disparity Map. 38th German Conference on Pattern Recognition. Springer, Hannover. https://arxiv.org/abs/1606.02092PDF icon Technical Report (2.34 MB)
Berger, J, Lenzen, F, Becker, F, Neufeld, A and Schnörr, C (2017). {Second-Order Recursive Filtering on the Rigid-Motion Lie Group SE(3) Based on Nonlinear Observations. J. Math. Imag. Vision. 58 102–129
Berger, J and Schnörr, C (2016). Joint Recursive Monocular Filtering of Camera Motion and Disparity Map. 38th German Conference on Pattern Recognition
Berger, J, Neufeld, A, Becker, F, Lenzen, F and Schnörr, C (2015). Second Order Minimum Energy Filtering on SE(3) with Nonlinear Measurement Equations. Scale Space and Variational Methods in Computer Vision (SSVM 2015)
Berger, J, Lenzen, F, Becker, F, Neufeld, A and Schnörr, C (2015). Second-Order Recursive Filtering on the Rigid-Motion Lie Group SE(3) Based on Nonlinear Observations. http://arxiv.org/abs/1507.06810
Berger, J, Neufeld, A, Becker, F, Lenzen, F and Schnörr, C (2015). Second Order Minimum Energy Filtering on SE(3) with Nonlinear Measurement Equations. Scale Space and Variational Methods in Computer Vision (SSVM 2015). Springer International Publishing. http://dx.doi.org/10.1007/978-3-319-18461-6_32PDF icon Technical Report (364.01 KB)
Berger, J, Lenzen, F, Becker, F, Neufeld, A and Schnörr, C (2015). Second-Order Recursive Filtering on the Rigid-Motion Lie Group SE(3) Based on Nonlinear Observations. http://arxiv.org/abs/1507.06810PDF icon Technical Report (4.42 MB)
Berger, K, Meister, S, Nair, R and Kondermann, D (2013). A State of the Art Report on Kinect Sensor Setups in Computer Vision. Time-of-Flight and Depth Imaging. Sensors, Algorithms, and Applications. Springer. 8200 257-272
Berg, S, Kutra, D, Kroeger, T, Straehle, C N, Kausler, B X, Haubold, C, Schiegg, M, Ales, J, Beier, T, Rudy, M, Eren, K, Cervantes, J I, Xu, B, Beuttenmüller, F, Wolny, A, Zhang, C, Köthe, U, Hamprecht, F A and Kreshuk, A (2019). ilastik: interactive machine learning for (bio)image analysis. Nature Methods. 16 1226-1232

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