Publications

Schilling, H, Gutsche, M, Brock, A, Späth, D, Rother, C and Krispin, K (2020). Mind the Gap – A Benchmark for Dense Depth Prediction beyond Lidar. 2nd Workshop on Safe Artificial Intelligence for Automated Driving, in conjunction with CVPR 2020

Klar, M, Stybalkowski, P, Spies, H and Jähne, B (2002). A miniaturized 3-D particle-tracking velocimetry system to measure the pore flow within a gravel layer. Proc. 11th Int. Symp. Applications of Laser Techniques to Fluid Mechanics. 2.3. http://in3.dem.ist.utl.pt/lxlaser2002/papers.asp

Rother, C, Kohli, P, Feng, W and Jia, J (2010). Minimizing sparse higher order energy functions of discrete variables. 1382–1389

Enzweiler, M and Gavrila, D M (2008). A Mixed Generative-Discriminative Framework for Pedestrian Classification. Proc. Int. Conf. Comp. Vision and Patt. Recog. (CVPR)

Garbe, C S, Spies, H and Jähne, B (2002). Mixed OLS-TLS for the estimation of dynamic processes with a linear source term. Proceedings of the 24th DAGM Symposium on Pattern Recognition. Springer-Verlag. 2449 463--471

Wulf, M, Stiehl, H S and Schnörr, C (1999). A model of spatiotemporal receptive fields in the primate retina. Proc. 1st Göttingen Conf. German Neurosci. Soc.. II

Wulf, M, Stiehl, H S and Schnörr, C (1999). Modeling spatiotemporal receptive fields in the primate retina. Proc. Cognitive Neurosci. Conf. Hanse–Wissenschaftskolleg, Bremen, Germany

Herrmann, H and Jähne, B (1998). Modulare Software für die höherdimensionale Bildverarbeitung. 5. ABW-Workshop, TA Esslingen 20.--21.01.1998

van Halsema, D, Snoeij, P, Calkoen, C J, Oost, W A, Vogelzang, J and Jähne, B (1991). Modulation of the microwave backscatter by long gravity waves as measured in a very large wind/wave flume. Proc. IGARSS '91. 3 1293--1296

Enzweiler, M, Kanter, P and Gavrila, D M (2008). Monocular Pedestrian Recognition Using Motion Parallax. Proc. IEEE Symposium on Intelligent Vehicles. 792-797

Monroy, A, Bell, P and Ommer, B (2013). A Morphometric Approach to Reception Analysis of Premodern Art. Scientific Computing & Cultural Heritage

Technical Report (17.75 MB)

Cremers, D and Schnörr, C (2002). Motion Competition: Variational Integration of Motion Segmentation and Shape Regularization. Pattern Recognition, Proc. 24th DAGM Symposium. Springer, Zürich, Switzerland. 2449 472–480

Jähne, (1990). Motion determination in space-time images. Proc. Computer Vision -- ECCV 90, Lecture Notes in Computer Science 427. 161--173

Jähne, (1989). Motion determination in space-time images. Image Processing III, SPIE Proceeding 1135, international congress on optical science and engineering, Paris, 24-28 April 1989. 147--152

Kondermann, D, Kondermann, C, Berthe, A, Kertzscher, U and Garbe, C S (2008). Motion Estimation Based on a Temporal Model of Fluid Flows. 13th International Symposium on Flow Visualization. 1-10

Schnörr, C and Peckar, W (1995). Motion-Based Identification of Deformable Templates. Proc. 6th Int. Conf. on Computer Analysis of Images and Patterns (CAIP '95). Springer Verlag, Prague, Czech Republic. 970 122-129

Becker, M, Baron, M, Kondermann, D, Bussler, M and Helzle, V (2013). Movie Dimensionalization Via Sparse User Annotations. submitted to 3DTV-Con

Kondermann, D and Becker, M (2013). Movie Dimensionalization Via Sparse User Annotations. submitted to ICCV

Tourani, S, Shekhovtsov, A, Rother, C and Savchynskyy, B (2018). MPLP++: Fast, Parallel Dual Block-Coordinate Ascent for Dense Graphical Models. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 11208 LNCS 264–281

Kappes, J H, Schmidt, S and Schnörr, C (2010). MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation. European Conference on Computer Vision (ECCV). Springer Berlin / Heidelberg. 6313 735–747

Kappes, J H, Schmidt, S and Schnörr, C (2010). MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation. European Conference on Computer Vision (ECCV). Springer. 6313 735--747

Kappes, J H, Schmidt, S and Schnörr, C (2010). MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation. European Conference on Computer Vision (ECCV). Springer Berlin / Heidelberg. 6313 735--747

Technical Report (1.49 MB)

Geißler, P and Jähne, B (1997). A multi-camera system for in-shore measurements of bubble size distributions beneath breaking waves. Optical 3-D Measurement Techniques IV, Zurich, Sept. 29 - Oct. 2, 1997. Wichmann. 251--258

Balschbach, G, Klinke, J and Jähne, B (1998). Multichannel shape from shading techniques for moving specular surfaces. ECCV 1998. Springer, Berlin. 1407 170--184

Balschbach, G, Klinke, J and Jähne, B (1997). Multichannel shape from shading techniques for reconstruction of specular surfaces. Tagungsband Herbsttagung des Graduiertenkollegs "3D Bildanalyse und -synthese". H.-P. Seidel, B. Girod, H. Niemann (Hrsg.)

Lin, Z, Erz, M and Jähne, B (2010). Multi-frequency multi-sampling fluorescence lifetime imaging using a high-speed line-scan camera. Optics, Photonics, and Digital Technologies for Multimedia Applications, 12--15 April 2010, Brussels. 7723 77231S

Urban, G, Bendszus, M, Hamprecht, F A and Kleesiek, J (2014). Multi-modal Brain Tumor Segmentation using Deep Convolutional NeuralNetworks. MICCAI BraTS (Brain Tumor Segmentation) Challenge. Proceedings, winningcontribution. 31-35

Cremers, D, Sochen, N and Schnörr, C (2004). Multiphase Dynamic Labeling for Variational Recognition-Driven Image Segmentation. Computer Vision – ECCV 2004. Springer. 3024 74-86

Straehle, C N, Kandemir, M, Köthe, U and Hamprecht, F A (2014). Multiple instance learning with response-optimized random forests. ICPR. Proceedings. 3768 - 3773

Technical Report (296.66 KB)

Ommer, B and Malik, J (2009). Multi-scale Object Detection by Clustering Lines. Proceedings of the IEEE International Conference on Computer Vision. IEEE. 484--491

Technical Report (3.18 MB)

Hanselmann, M, Köthe, U, Renard, B Y, Kirchner, M, Heeren, R M A and Hamprecht, F A (2009). Multivariate Watershed Segmentation of Compositional Data. Proceedings of the 15th International Conference on Discrete Geometry for Computer Imagery (DGCI), in press. Springer. 5810 180-192

Technical Report (1.25 MB)

Wolf, S, Pape, C, Bailoni, A, Rahaman, N, Kreshuk, A, Köthe, U and Hamprecht, F A (2018). The Mutex Watershed: Efficient, Parameter-Free Image Partitioning. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 11208 LNCS 571–587. http://arxiv.org/abs/1904.12654

Heiler, M and Schnörr, C (2003). Natural Statistics for Natural Image Segmentation. Proc. IEEE Int. Conf. Computer Vision (ICCV 2003). Nice, France. 1259-1266

Rombach, R, Esser, P and Ommer, B (2020). Network Fusion for Content Creation with Conditional INNs. CVPRW 2020 (AI for Content Creation). https://compvis.github.io/network-fusion/

Jähne, (1987). Neue Ansätze zur Bildfolgenanalyse. Proc. 9. DAGM-Symposium zur Mustererkennung 1987. Springer. 149 287

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