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Author Title [ Type(Desc)] Year
Conference Paper
Hodaň, T, Michel, F, Brachmann, E, Kehl, W, Buch, A Glent, Kraft, D, Drost, B, Vidal, J, Ihrke, S, Zabulis, X, Sahin, C, Manhardt, F, Tombari, F, Kim, T Kyun, Matas, J and Rother, C (2018). BOP: Benchmark for 6D object pose estimation. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 11214 LNCS 19–35. http://arxiv.org/abs/1808.08319
Behl, A, Hosseini Jafari, O, Mustikovela, S Karthik, Abu Alhaija, H, Rother, C and Geiger, A (2017). Bounding Boxes, Segmentations and Object Coordinates: How Important is Recognition for 3D Scene Flow Estimation in Autonomous Driving Scenarios?. Proceedings of the IEEE International Conference on Computer Vision. 2017-Octob 2593–2602
Behl, A, Hosseini Jafari, O, Mustikovela, S Karthik, Abu Alhaija, H, Rother, C and Geiger, A (2017). Bounding Boxes, Segmentations and Object Coordinates: How Important is Recognition for 3D Scene Flow Estimation in Autonomous Driving Scenarios?. Proceedings of the IEEE International Conference on Computer Vision. 2017-Octob 2593–2602
Petra, S, Schnörr, C, Becker, F and Lenzen, F (2013). B-SMART: Bregman-Based First-Order Algorithms for Non-Negative Compressed Sensing Problems. Proceedings of the 4th International Conference on Scale Space and Variational Methods in Computer Vision (SSVM) 2013. Springer. 7893 110-124PDF icon Technical Report (1.15 MB)
Petra, S, Schnörr, C, Becker, F and Lenzen, F (2013). B-SMART: Bregman-Based First-Order Algorithms for Non-Negative Compressed Sensing Problems. Proceedings of the 4th International Conference on Scale Space and Variational Methods in Computer Vision SSVM. 110-124
Heikkonen, J, Koikkalainen, P and Schnörr, C (1994). Building Trajectories via Selforganization from Spatiotemporal Features. 12th Int. Conf. on Pattern Recognition. Jerusalem, Israel
Kappes, J H, Savchynskyy, B and Schnörr, C (2012). A Bundle Approach To Efficient MAP-Inference by Lagrangian Relaxation. CVPR. Proceedings. 1688-1695
Kappes, J H, Savchynskyy, B and Schnörr, C (2012). A Bundle Approach To Efficient MAP-Inference by Lagrangian Relaxation. CVPRPDF icon Technical Report (430.63 KB)
Jähne, B and Schultz, H (1992). Calibration and accuracy of optical slope measurements for short wind waves. Optics of the Air-Sea Interface: Theory and Measurements. 1749 222--233
Mustikovela, S Karthik, Yang, M Ying and Rother, C (2016). Can ground truth label propagation from video help semantic segmentation?. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 9915 LNCS 804–820
Zechmann, C M, Kelm, B Michael, Zamecnik, P, Ikinger, U, Waldherr, R, Röll, S, Delorme, S, Hamprecht, F A and Bachert, P (2006). Can man still beat the machine? Automated vs. manual pattern recognition of 3D MRSI data of prostate cancer patients. Proceedings of the 16th ISMRMPDF icon Technical Report (664.38 KB)
Maier-Hein, L, Mersmann, S, Kondermann, D, Bodenstedt, S, Sanchez, A, Stock, C, Kenngott, H, Eisenmann, M and Speidel, S (2014). Can masses of non-experts train highly accurate image classifiers? A crowdsourcing approach to instrument segmentation in laparoscopic images. MICCAI
Straehle, C N, Köthe, U, Knott, G W and Hamprecht, F A (2011). Carving: Scalable Interactive Segmentation of Neural Volume Electron Microscopy Images. MICCAI 2011, Proceedings. Springer. 6891 653-660PDF icon Technical Report (1.69 MB)
Welbl, J (2014). Casting Random Forests as Artificial Neural Networks (and Profiting from It). GCPR. Proceedings. 765-771PDF icon Technical Report (376.24 KB)
Zhang, C, Yarkony, J and Hamprecht, F A (2014). Cell detection and segmentation using correlation clustering. MICCAI. Proceedings. Springer. 9-16PDF icon Technical Report (8.06 MB)
Mackowiak, R, Lenz, P, Ghori, O, Diego, F, Lange, O and Rother, C (2019). CEREALS - Cost-Effective REgion-based Active Learning for Semantic Segmentation. British Machine Vision Conference 2018, BMVC 2018
Schmund, D, Münsterer, T, Lauer, H, Jähne, B and Jähne, B (1995). The circular wind wave facilities at the University of Heidelberg. Air-Water Gas Transfer - Selected papers from the Third International Symposium on Air-Water Gas Transfer. AEON. 505--516
Kelm, B Michael, Menze, B H, Neff, T, Zechmann, C M and Hamprecht, F A (2006). CLARET: a tool for fully automated evaluation of MRSI with pattern recognition methods.. Bildverarbeitung für die Medizin 2006 - Algorithmen, Systeme, Anwendungen. Springer. 51-55. http://www.efmi-wg-mip.net/service/bvm2006PDF icon Technical Report (275.25 KB)
Heers, J, Schnörr, C and Stiehl, H S (1998). A class of parallel algorithms for nonlinear variational image segmentation. Proc. Noblesse Workshop on Non–Linear Model Based Image Analysis (NMBIA'98). Glasgow, Scotland
Menze, B H, Wormit, M, Bachert, P, Lichy, M P, Schlemmer, H - P and Hamprecht, F A (2004). Classification of in vivo magnetic resonance spectra. Classification in ubiquitous challenge: Proceedings of the GfKl 2004. Springer. 362-369PDF icon Technical Report (240.1 KB)
Menze, B H and Ur, J A (2007). Classification of multispectral ASTER imagery in the archaeological survey for settlement sites of the Near East. Proc 10th International Symposium on Physical Measurements and Signature in Remote Sensing (ISPMRS 07), Davos, Switzerland. International Archives of the Photogrammetry, Remote Sensing and Spatial Information SciencesPDF icon Technical Report (920.71 KB)
Kaster, F O, Kelm, B Michael, Zechmann, C M, Weber, M - A, Hamprecht, F A and Nix, O (2009). Classification of Spectroscopic Images in the DIROlab Environment. World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany. Springer. 25/V 252--255PDF icon Technical Report (145.73 KB)
Bautista, M, Sanakoyeu, A, Sutter, E and Ommer, B (2016). CliqueCNN: Deep Unsupervised Exemplar Learning. Proceedings of the Conference on Advances in Neural Information Processing Systems (NIPS). MIT Press, Barcelona. https://arxiv.org/abs/1608.08792PDF icon Article (5.79 MB)
Long, S R and Klinke, J (2002). A closer look at short waves generated by wave interactions with adverse currents. Gas Transfer at Water Surfaces. American Geophysical Union. 127 121--128
Kannan, A, Winn, J and Rother, C (2007). Clustering appearance and shape by learning jigsaws. Advances in Neural Information Processing Systems. 657–664
Kannan, A, Winn, J and Rother, C (2007). Clustering appearance and shape by learning jigsaws. Advances in Neural Information Processing Systems. 657–664
Geese, M, Ruhnau, P and Jähne, B (2012). CNN based dark signal non-uniformity estimation. Cellular Nanoscale Networks and Their Applications (CNNA), 2012 13th International Workshop on. 1--6
Waas, S and Jähne, B (1996). Combined height/slope/curvature measurements of short ocean wind waves. Proc.\ The Air-Sea Interface, Radio and Acoustic Sensing, Turbulence and Wave Dynamics, Marseille, 24--30. June 1993. RSMAS, University of Miami. 383--388
Waas, S and Jähne, B (1992). Combined slope-height measurements of short wind waves: first results from field and laboratory measurements. Optics of the Air-Sea Interface: Theory and Measurements. 1749 295--306
Rocholz, R, Wanner, S, Schimpf, U and Jähne, B (2011). Combined visualization of wind waves and water surface temperature. Gas Transfer at Water Surfaces 2010. 496--506. http://hdl.handle.net/2433/156156
Hering, F, Wierzimok, D, Melville, W K and Jähne, B (1996). Combined wave and flow field visualization for investigation of short-wave/long-wave interaction. Proc.\ The Air-Sea Interface, Radio and Acoustic Sensing, Turbulence and Wave Dynamics, Marseille, 24--30. June 1993. RSMAS, University of Miami. 133--138
Kelm, B Michael, Pal, C and McCallum, A (2006). Combining Generative and Discriminative Methods for Pixel Classification with Multi-Conditional Learning.. ICPR 2006. 2 828-832PDF icon Technical Report (114.99 KB)
Bruhn, A, Weickert, J and Schnörr, C (2002). Combining the Advantages of Local and Global Optic Flow Methods. Pattern Recognition, Proc. 24th DAGM Symposium. Springer, Zürich, Switzerland. 2449 454–462
Jähne, (1994). A comparative analytical study of low-level motion estimators in space-time images. Proc. 16. DAGM-Symposium Mustererkennung
Kräuter, C, Richter, K E, Jähne, B, Mesarchaki, E and Williams, J (2011). A comparative lab study of tansfer velocities of volatile tracers with widely varying solubilities. DPG Frühjahrstagung Dresden, Fachverband Umweltphysik. http://www.dpg-verhandlungen.de/year/2011/conference/dresden/part/up/session/1/contribution/29

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