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Güssefeld, B, Honauer, K and Kondermann, D (2016). Creating Feasible Reflectance Data for Synthetic Optical Flow Datasets. Advances in Visual Computing - 12th International Symposium, {ISVC} 2016, Las Vegas, NV, USA, December 12-14, 2016, Proceedings, Part {I}

Jähne, B, Waas, S and Klinke, J (1992). A critical theoretical review of optical techniques for short ocean wave measurements. Optics of the Air-Sea Interface: Theory and Measurements. 1749 204--215

Sayed, N, Brattoli, B and Ommer, B (2018). Cross and Learn: Cross-Modal Self-Supervision. German Conference on Pattern Recognition (GCPR) (Oral). Stuttgart, Germany. https://arxiv.org/abs/1811.03879v1

Article (891.47 KB)

Oral slides (9.17 MB)

Fehr, J, Reisert, M and Burkhardt, H (2009). Cross-Correlation and Rotation Estimation of Local 3D Vector FieldPatches. Proceedings of the ISVC 2009, Part I. Springer. 5875 287-296

Schlesinger, D, Jug, F, Myers, G, Rother, C and Kainmueller, D (2017). Crowd sourcing image segmentation with iaSTAPLE. Proceedings - International Symposium on Biomedical Imaging. 401–405

Maier-Hein, L, Mersmann, S, Kondermann, D, Stock, C, Kenngott, H, Sanchez, A, Wagner, M, Preukschas, A, Wekerle, A - L, Helfert, S, Bodenstedt, S and Speidel, S (2014). Crowdsourcing for reference correspondence generation in endoscopic images. MICCAI

Shekhovtsov, A, Kohli, P and Rother, C (2012). Curvature prior for MRF-based segmentation and shape inpainting. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7476 LNCS 41–51. http://arxiv.org/abs/1109.1480

Shekhovtsov, A, Kohli, P and Rother, C (2012). Curvature prior for MRF-based segmentation and shape inpainting. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7476 LNCS 41–51. www.research.microsoft.com/vision/cambridge http://www.cs.ucl.ac.uk/staff/V.Kolmogorov/papers/StereoSegmentation_PAMI06.pdf%5Cnpapers3://publication/uuid/F008E9F4-510D-4478-A3C0-1BFB22F6AEA0

Shekhovtsov, A, Kohli, P and Rother, C (2012). Curvature prior for MRF-based segmentation and shape inpainting. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7476 LNCS 41–51

Beier, T, Kröger, T, Kappes, J H, Köthe, U and Hamprecht, F A (2014). Cut, Glue and Cut: A Fast, Approximate Solver for Multicut Partitioning. 2014 {IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR} 2014, Columbus, OH, USA, June 23-28, 2014. http://dx.doi.org/10.1109/CVPR.2014.17

Technical Report (10.06 MB)

Honauer, K, Johannsen, O, Kondermann, D and Goldlücke, B (2016). A Dataset and Evaluation Methodology for Depth Estimation on 4D Light Fields. Computer Vision - ACCV 2016 : 13th Asian Conference on Computer Vision, Taipei, Taiwan, November 20-24, 2016, Revised Selected Papers, Part III. Springer, Cham

Wanner, S, Meister, S and Goldlücke, B (2013). Datasets and Benchmarks for Densely Sampled 4D Light Fields. Vision, Modeling & Visualization. 225--226

Nowozin, S, Rother, C, Bagon, S, Sharp, T, Yao, B and Kohli, P (2011). Decision tree fields. Proceedings of the IEEE International Conference on Computer Vision. 1668–1675

Becker, F and Schnörr, C (2008). Decomposition of Quadratric Variational Problems. Pattern Recognition -- 30th DAGM Symposium. Springer Verlag. 5096 325--334

Technical Report (1.29 MB)

Becker, F and Schnörr, C (2008). Decomposition of Quadratric Variational Problems. Pattern Recognition -- 30th DAGM Symposium. 5096 325--334

Li, W, Hosseini Jafari, O and Rother, C (2019). Deep Object Co-segmentation. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 11363 LNCS 638–653

Ufer, N and Ommer, B (2017). Deep Semantic Feature Matching. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

article (8.88 MB)

Bautista, M, Sanakoyeu, A and Ommer, B (2017). Deep Unsupervised Similarity Learning using Partially Ordered Sets. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

deep_unsupervised_similarity_learning_cvpr_2017_paper.pdf (905.82 KB)

van Vliet, P, Hering, F, Jähne, B and Jähne, B (1995). Delft Hydraulics Large Wind-Wave Flume. Air-Water Gas Transfer---Selected Papers from the Third International Symposium of Air--Water Gas Transfer in Heidelberg. AEON. 499--502

Lou, X, Kaster, F O, Lindner, M, Kausler, B X, Köthe, U, Höckendorf, B, Wittbrodt, J, Jänicke, H and Hamprecht, F A (2011). DELTR: Digital Embryo Lineage Tree Reconstructor. Eighth IEEE International Symposium on Biomedical Imaging (ISBI). Proceedings. 1557-1560

Technical Report (1.44 MB)

Lenzen, F, Kim, K I, Schäfer, H, Nair, R, Meister, S, Becker, F and Garbe, C S (2013). Denoising Strategies for Time-of-Flight Data. Time-of-Flight Imaging: Algorithms, Sensors and Applications. Springer. 8200 24-25

Lenzen, F, Schäfer, H and Garbe, C S (2011). Denoising Time-Of-Flight Data with Adaptive Total Variation. Proceedings ISVC. Springer. 337-346

Spies, H and Garbe, C S (2002). Dense parameter fields from total least squares. Proceedings of the 24th DAGM Symposium on Pattern Recognition. Springer. LNCS 2449 379--386

Spies, H, Jähne, B and Barron, J L (2000). Dense range flow from depth and intensity data. ICPR. 131--134

Zheng, S, Cheng, M Ming, Warrell, J, Sturgess, P, Vineet, V, Rother, C and Torr, P H S (2014). Dense semantic image segmentation with objects and attributes. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 3214–3221. http://www.robots.ox.ac.uk/˜tvg/http://tu-dresden.de/inf/cvld

Spies, H, Kirchgeßner, N, Scharr, H and Jähne, B (2000). Dense structure estimation via regularised optical flow. VMV 2000. Aka GmbH, Berlin. 57--64

Schäfer, H, Lenzen, F and Garbe, C S (2013). Depth and Intensity Based Edge Detection in Time-of-Flight Images. 3DV-Conference, 2013 International Conference on. 111-118

Technical Report (1.85 MB)

Schäfer, H, Lenzen, F and Garbe, C S (2013). Depth and Intensity Based Edge Detection in Time-of-Flight Images. 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT), 2013 International Conference on. IEEE. 111-118

Jähne, B and Geißler, P (1994). Depth from focus with one image. Proc. Conference on Computer Vision and Pattern Recognition (CVPR '94), Seattle, 20.-23. June 1994. 713--717

Hornáček, M, Rhemann, C, Gelautz, M and Rother, C (2013). Depth super resolution by rigid body self-similarity in 3D. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 1123–1130

Geißler, P, Scholz, T, Jähne, B, Schmidt, C, Suhr, H and Wehnert, G (1995). Depth-from-Focus Verfahren zur absoluten Größen- und Konzentrationsbestimmung kleiner Teilchen. Bildverarbeitung'95 - Forschen, Entwickeln, Anwenden. Technische Akademie Esslingen. 365--380

Geißler, P, Jähne, B and Pöppl, S J (1993). Depth-from-focus zur Bestimmung der Konzentration und Größe von Gasblasen. Proc. 15. DAGM-Symposium Mustererkennung. Springer. 560--567

Jähne, (2013). Der Standard EMVA 1288 zur Charakterisierung von Kameras und Bildsensoren: von 2D- zu 3D-Kameras. Photogrammetrie, Laserscanning, Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2013. Wichmann. 388--399. http://www.ub.uni-heidelberg.de/archiv/17699

Bock, E J, Edson, J B, Frew, N M, Karachintsev, A, McGilles, W R, Nelson, R K, Hansen, K, Jähne, B, Hara, T, Uz, B M, Jähne, B, Dieter, J, Klinke, J and Haußecker, H (1995). Description of the science plan for the April 1995 CoOP experiment, `gas transfer in coastal waters', performed from the research vessel New Horizon. Air-Water Gas Transfer, Selected Papers, 3rd Intern. Symp. on Air-Water Gas Transfer. AEON. 801--810

Bruhn, A, Jakob, T, Fischer, M, Kohlberger, T, Weickert, J, Brüning, U and Schnörr, C (2002). Designing 3–D Nonlinear Diffusion Filters for High Performance Cluster Computing. Pattern Recognition, Proc. 24th DAGM Symposium. Springer, Zürich, Switzerland. 2449 290–297

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