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M. Heiler and Schnörr, C., “Reverse-Convex Programming for Sparse Image Codes”, in Proc. Int. Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'05), 2005, vol. 3757, pp. 600-616.

A. Vianello, Ackermann, J., Diebold, M., and Jähne, B., “Robust Hough transform based 3D reconstruction from circular light fields”, in Conference on Computer Vision and Pattern Recognition (CVPR), 2018.

B. Antic and Ommer, B., “Robust Multiple-Instance Learning with Superbags”, in Proceedings of the Aian Conference on Computer Vision (ACCV) (Oral), 2012, p. 242--255.

Technical Report (319.58 KB)

F. Hering, Merle, M., Wierzimok, D., and Jähne, B., “A robust technique for tracking particles over long image sequences”, in Proc. ISPRS Intercommission Workshop `From Pixels to Sequences', Zurich, March 22 - 24, 1995, In Int'l Arch. of Photog. and Rem. Sens., 1995, vol. XXX-5W1, p. 74--79.

B. Jähne, Haußecker, H., Hering, F., Balschbach, G., Klinke, J., Lell, M., Schmund, D., Schultz, M., Schurr, U., Stitt, M., and Platt, U., “The role of active vision in exploring growth, transport, and exchange processes”, in Aktives Sehen in technischen und biologischen Systemen, Workshop der GI-Fachgruppe 1.0.4. Bildverstehen Hamburg, 3--4. December 1996, 1996, vol. 4, p. 194--202.

N. Kirchgeßner, Spies, H., Scharr, H., and Schurr, U., “Root Growth Analysis in Physiological Coordinates”, in International Conference on Image Analysis and Processing (ICIAP'01), 2001.

N. Kirchgeßner, Spies, H., Scharr, H., and Schurr, U., “Root Growth Measurements in Object Coordinates”, in Proceedings of the 23th DAGM Symposium on Pattern Recognition, 2001.

O. Friedrich, Weber, C., Both, M., von Wegner, F., Chamberlain, J. S., Garbe, C. S., and Fink, R. H. A., “Sarcomere Structure and Motor-Protein Function in an Animal Model of Duchenne Muscular Dystrophy (mdx mouse)”, in 87th Annual Meeting of the German Physiological Society, 2008.

M. Geese, Ruhnau, P., and Jähne, B., “Scene based maximum likelihood PRNU and DSNU non uniformity correction”, in Forum Bildverarbeitung, 2012, p. 71--82.

A. Mansfield, Gehler, P., Van Gool, L., and Rother, C., “Scene carving: Scene consistent image retargeting”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010, vol. 6311 LNCS, pp. 143–156.

K. E. Richter, Rocholz, R., and Jähne, B., “The Schmidt Number Dependency of Air-Sea Gas Exchange with Varying Surfactant Coverage”, in SOLAS Open Science Conference, Washington State, USA, 2012.

J. Berger, Neufeld, A., Becker, F., Lenzen, F., and Schnörr, C., “Second Order Minimum Energy Filtering on SE(3) with Nonlinear Measurement Equations”, in Scale Space and Variational Methods in Computer Vision (SSVM 2015), 2015.

Technical Report (364.01 KB)

J. Berger, Neufeld, A., Becker, F., Lenzen, F., and Schnörr, C., “Second Order Minimum Energy Filtering on SE(3) with Nonlinear Measurement Equations”, in Scale Space and Variational Methods in Computer Vision (SSVM 2015), 2015.

C. N. Straehle, Köthe, U., Briggman, K., Denk, W., and Hamprecht, F. A., “Seeded watershed cut uncertainty estimators for guided interactive segmentation”, in CVPR 2012. Proceedings, 2012, pp. 765 - 772.

Technical Report (2.84 MB)

L. Kostrykin, Schnörr, C., and Rohr, K., “Segmentation of Cell Nuclei Using Intensity-Based Model Fitting and Sequential Convex Programming”, in Proc. ISBI, 2018.

P. Markowsky, Reith, S., Zuber, T. E., König, R., Rohr, K., and Schnörr, C., “Segmentation of cell structure using model-based set covering with iterative reweighting”, in Proc. ISBI, 2017.

B. Andres, Köthe, U., Helmstaedter, M., Denk, W., and Hamprecht, F. A., “Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification”, in Pattern Recognition. 30th DAGM Symposium Munich, Germany, June 10-13, 2008. Proceedings, 2008, vol. 5096, pp. 142-152.

Technical Report (1.21 MB)

C. Schnörr, “Segmentation of Visual Motion by Minimizing Convex Non-Quadratic Functionals”, in 12th Int. Conf. on Pattern Recognition, Jerusalem, Israel, 1994.

C. Leue, Geißler, P., Jähne, B., Jähne, B., Geißler, P., and Haußecker, H., “Segmentierung von Partikelbildern in der Strömungsvisualisierung”, in Proceedings of 18th DAGM-Symposium Mustererkennung, 1996, p. 118--129.

B. Andres, Hamprecht, F. A., and Garbe, C. S., “Selection of Local Optical Flow Models by Means of Residual Analysis”, in Pattern Recognition, 2007, vol. 4713, pp. 72-81.

Technical Report (229.64 KB)

B. Andres, Garbe, C. S., Schnörr, C., and Jähne, B., “Selection of local optical flow models by means of residual analysis”, in Proceedings of the 29th DAGM Symposium on Pattern Recognition, 2007, p. 72--81.

Ö. Sümer, Dencker, T., and Ommer, B., “Self-supervised Learning of Pose Embeddings from Spatiotemporal Relations in Videos”, in Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2017.

Paper (3.98 MB)

Supplementary Material (3.36 MB)

S. K. Mustikovela, Jampani, V., De Mello, S., Liu, S., Iqbal, U., Rother, C., and Kautz, J., “Self-Supervised Viewpoint Learning From Image Collections”, in CONSAC, 2020.

PDF (8.77 MB)

A. Zouhar, Rother, C., and Fuchs, S., “Semantic 3-D labeling of ear implants using a global parametric transition prior”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, vol. 9350, pp. 177–184.

A. Drory, Haubold, C., Avidan, S., and Hamprecht, F. A., “Semi-Global Matching: A Principled Derivation in Terms of Message Passing”, in GCPR. Proceedings, 2014, pp. 43-53.

Technical Report (2.6 MB)

L. Görlitz, Menze, B. H., Weber, M. - A., and Kelm, B. Michael, “Semi-Supervised Tumor Detection in MRSI With Discriminative Random Fields”, in Pattern Recognition, 2007, vol. 4713, pp. 224-233.

Technical Report (872.46 KB)

S. Gerloff, Hagemann, A., Schnörr, C., Tieck, S., Stiehl, H. S., Dombrowski, R., Dreyer, M., and Wiesendanger, R., “Semi–Automated Analysis of SXM Images”, in Proc. 9th Int. Conf. on Scanning Tunneling Microscopy/Spectroscopy and Related Techniques (STM'97), Hamburg, Germany, 1997.

B. Jähne, Waas, S., and Klinke, J., “Shape from shading techniques for short ocean wind waves”, in Imaging in Transport Processes, 1993, p. 269--281.

A. Monroy, Bell, P., and Ommer, B., “Shaping Art with Art: Morphological Analysis for Investigating Artistic Reproductions”, in Proceedings of the European Conference on Computer Vision, Workshop on VISART, 2012, vol. 7583, p. 571--580.

Technical Report (7 MB)

B. Jähne, “Simulation der Austauschprozesse an der Ozeanoberfläche im Labor: das neue Heidelberger Aeolotron”, in Verhandlungen der Deutschen Physikalischen Gesellschaft, Spring Conference, Hamburg, 26.-30.03.2001, 2001.

S. Meister, Nair, R., and Kondermann, D., “Simulation of Time-of-Flight Sensors using Global Illumination”, in Vision, Modeling and Visualization (VMV), 2013 International Workshop on. Proceedings, 2013, pp. 33-40.

M. Klar, Jehle, M., Detert, M., Jirka, G. H., Jähne, B., Köhler, H. - J., and Wenka, T., “Simultaneous 3D PTV and micro-pressure sensor equipment for flow analysis in subsurface gravel layer”, in Proc. of River Flow 2004, 2004, p. 703--712.

A. G. Herzog, Friedl, F., and Jähne, B., “Simultaneous high-resolution LIF measurements of dissolved gas concentration fields and measurements of wave slope at a wavy free water surface with wind-induced turbulence”, in 15h Int. Symp on Appl. Laser Techniques to Fluid Mechanics, Lisbon, Portugal, July 05--08, 2010, 2010.

B. Jähne, “Simultaneous measurements of solubilities and diffusion coeffcients of volatile species in liquids”, in 7th SOPRAN Annual Meeting, Bremen, Germany, 25-26 March 2014, 2014.

B. Jähne and Herrmann, H., “Softwarekonzepte und Algorithmen für die 3D-Bildverarbeitung”, in 4. ABW Workshop, TA Esslingen 22.--23.01.1997, 1997.

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