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Maier-Hein, L, Franz, A M, Fangerau, M, Schmidt, M, Seitel, A, Mersmann, S, Kilgus, T, Groch, A, Yung, K, Santos, T R dos and Meinzer, H - P (2011). Towards mobile augmented reality for on-patient visualization of medical images. Bildverarbeitung für die Medizin (2011). Springer. 389--393
Jähne, B and Garbe, C S (2003). Towards objective performance analysis for estimation of complex motion: analytic motion modeling, filter optimization, and test sequences. In Proceedings of IEEE International Conference on Image Processing. ./pdf/2003/barth_ICIP2003.pdf:PDF
Cremers, D, Sochen, N and Schnörr, C (2003). Towards Recognition-Based Variational Segmentation Using Shape Priors and Dynamic Labeling. Scale Space Methods in Computer Vision. Springer. 2695 388--400PDF icon Technical Report (451.82 KB)
Cremers, D, Sochen, N and Schnörr, C (2003). Towards Recognition-Based Variational Segmentation Using Shape Priors and Dynamic Labeling. Scale Space Methods in Computer Vision. Springer. 2695 388–400
Esparza, J, Helmle, M and Jähne, B (2014). Towards surround stereo vision: analysis of a new surround view camera configuration for driving asistance applications. 17th International Conference on Intelligent Transportation Systems (ITSC 2014)
Xiao, S (2019). Tracking Dividing Cells Using Spatio-Temporal Embeddings. Heidelberg University
Wierzimok, D, Hering, F and Brunswig, F (1992). Tracking in Strömungsbildfolgen. Proc. 14. DAGM-Symposium Mustererkennung. Springer
Fiaschi, L, Diego, F, Grosser, K - H, Schiegg, M, Köthe, U, Zlatic, M and Hamprecht, F A (2014). Tracking indistinguishable translucent objects over time using weakly supervised structured learning. CVPR. Proceedings. 2736 - 2743PDF icon Technical Report (1.47 MB)
Lenor, S, Martini, J, Jähne, B, Stopper, U, Weber, S and Ohr, F (2014). Tracking-based visibility estimation. Pattern Recognition, 36th German Conference, GCPR 2014, Münster, Germany, September 2-5, 2014. Springer. 8753 365--376
Kausler, B X (2013). Tracking-by-Assignment as a Probabilistic Graphical Model with Applications in Developmental Biology. University of Heidelberg
Bell, P and Ommer, B (2015). Training Argus. Kunstchronik. Monatsschrift für Kunstwissenschaft, Museumswesen und Denkmalpflege. Zentralinstitut für Kunstgeschichte. 68 414--420
Jähne, (1985). Transfer processes across the free water interface. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ. Heidelberg. Habilitation
Jähne, B and Schwarzkopf, P (2009). Transparency for Industrial Cameras and Sensors. http://www.gitverlag.com/de/print/4/18/issues/2009/3381.html
Jähne, (2007). Transport At The Air Sea Interface --- Measurements, Models And Parameterizations. Springer. http://hci.iwr.uni-heidelberg.de/publications/dip/2007/TASI/index.html
Garbe, C S, Flatow, F, Klinger, M, Schepanski, K, Tegen, I and Rannacher, R (2009). Transport of dust across the Sahara from satellite image sequence analysis. Eos Transactions. 90 EP21A-0565
Garbe, C S, Flatow, F, Klinger, M, Schepanski, K, Tegen, I and Rannacher, R (2009). Transport of Sahara dust into the Atlantic Ocean from satellite image sequence analysis. SOLAS Open Science Conference. 27
Glocker, B, T. Heibel, H, Navab, N, Kohli, P and Rother, C (2010). TriangleFlow: Optical flow with triangulation-based higher-order likelihoods. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6313 LNCS 272–285. http://vision.middlebury.edu/flow/
Jähne, (1982). Trockene Deposition von Gasen über Wasser (Gasaustausch). Austausch von Luftverunreinigungen an der Grenzfläche Atmospäre/Erdoberfläche, Zwischenbericht für das Umweltbundesamt zum Teilprojekt 1: Deposition von Gasen, BleV-R-64.284-2. Battelle Institut
Schilling, H, Diebold, M, Rother, C and Jähne, B (2018). Trust your Model: Light Field Depth Estimation with inline Occlusion Handling. CVPR. ProceedingsPDF icon Technical Report (5.46 MB)
Schilling, H, Diebold, M, Rother, C and Jähne, B (2018). Trust your Model: Light Field Depth Estimation with Inline Occlusion Handling. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 4530–4538
Jähne, B and Riemer, K (1990). Two-dimensional wave number spectra of small-scale water surface waves. J. Geophys. Res. 95 11531--11646
Hader, S and Hamprecht, F A (2004). Two-Stage Classification with Automatic Feature Selection for an Industrial Application. Classification, the ubiquitous challenge: Proceedings of GfKl 2004. Springer. 137-144PDF icon Technical Report (518.16 KB)
Peckar, W, Schnörr, C, Rohr, K and Stiehl, H S (1997). Two-Step Parameter-Free Elastic Image Registration with Prescribed Point Displacements. Proc. 9th Int. Conf. on Image Analysis and Processing (ICIAP'97). Florence, Italy
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Damrich, S and Hamprecht, F H (2021). UMAP does not reproduce high-dimensional similarities due to negative sampling. arXiv preprint
Brachmann, E, Michel, F, Krull, A, Yang, M Ying, Gumhold, S and Rother, C (2016). Uncertainty-Driven 6D Pose Estimation of Objects and Scenes from a Single RGB Image. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2016-Decem 3364–3372
Brachmann, E, Michel, F, Krull, A, Yang, M Ying, Gumhold, S and Rother, C (2016). Uncertainty-Driven 6D Pose Estimation of Objects and Scenes from a Single RGB Image. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2016-Decem 3364–3372
Richmond, D, Kainmueller, D, Glocker, B, Rother, C and Myers, G (2015). Uncertainty-driven forest predictors for vertebra localization and segmentation. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 9349 653–660
Bellagente, M, Haußmann, M, Luchmann, M and Plehn, T (2021). Understanding Event-Generation Networks via Uncertainties. arXiv preprint. https://arxiv.org/abs/2104.04543v1
Blattmann, A, Milbich, T, Dorkenwald, M and Ommer, B (2021). Understanding Object Dynamics for Interactive Image-to-Video Synthesis. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). https://arxiv.org/abs/2106.11303v1
Kirk, D S, Sellen, A J, Rother, C and Wood, K R (2006). Understanding photowork. Conference on Human Factors in Computing Systems - Proceedings. 2 761–770
Lifermann, A, Jähne, B and Ramamonjiarisoa, A (1987). Une ètude en soufflerie de la rèflexion des hyperfrèquences par des champs de houles et de vagues. Oceanologia Acta. SP 15--22
Schnörr, (1994). Unique Reconstruction of Piecewise Smooth Images by Minimizing Strictly Convex Non-Quadratic Functionals. 4 189–198
Zern, A, Zisler, M, Petra, S and Schnörr, C (2020). Unsupervised Assignment Flow: Label Learning on Feature Manifolds by Spatially Regularized Geometric Assignment. Journal of Mathematical Imaging and Vision. https://doi.org/10.1007/s10851-019-00935-7
Zern, A, Zisler, M, Petra, S and Schnörr, C (2019). Unsupervised Assignment Flow: Label Learning on Feature Manifolds by Spatially Regularized Geometric Assignment. preprint: arXiv. https://arxiv.org/abs/1904.10863
Brattoli, B, Büchler, U, Dorkenwald, M, Reiser, P, Filli, L, Helmchen, F, Wahl, A - S and Ommer, B (2021). Unsupervised behaviour analysis and magnification (uBAM) using deep learning. Nature Machine Intelligence. https://rdcu.be/ch6pL

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