Publications

2021

A. Vijayan, Tofanelli, R., Strauss, S., Cerrone, L., Wolny, A., Strohmeier, J., Kreshuk, A., Hamprecht, F. A., Smith, R. S., and Schneitz, K., “A Digital 3D Reference Atlas Reveals Cellular Growth Patterns Shaping the Arabidopsis Ovule”, eLife, 2021.

A. Sanakoyeu, Ma, P., Tschernezki, V., and Ommer, B., “Improving Deep Metric Learning by Divide and Conquer”, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.

C. Pape, Remme, R., Wolny, A., Olberg, S., Wolf, S., Cerrone, L., Cortese, M., Klaus, S., Lucic, B., Ullrich, S., Anders-Össwein, M., Wolf, S., Cerikan, B., Neufeldt, C. J., Ganter, M., Schnitzler, P., Merle, U., Lusic, M., Boulant, S., Stanifer, M., Bartenschlager, R., Hamprecht, F. A., Kreshuk, A., Tischer, C., Kräusslich, H. - G., Müller, B., and Laketa, V., “Microscopy-based assay for semi-quantitative detection of SARS-CoV-2 specific antibodies in human sera”, BioEssays, vol. 43, no. 3, 2021.

2020

A. Wolny, Cerrone, L., Vijayan, A., Tofanelli, R., Vilches-Barro, A., Louveaux, M., Wenzel, C., Strauss, S., Wilson-Sanchez, D., Lymbouridou, R., Steigleder, S. S., Pape, C., Bailoni, A., Duran-Nebreda, S., Bassel, G. W., Lohmann, J. U., Tsiantis, M., Hamprecht, F. A., Schneitz, K., Maizel, A., and Kreshuk, A., “Accurate and Versatile 3D Segmentation of Plant Tissues at Cellular Resolution”, eLife, vol. 9, 2020.

S. Bollweg, Haußmann, M., Kasieczka, G., Luchmann, M., Plehn, T., and Thompson, J., “Deep-Learning Jets with Uncertainties and More”, SciPost Phys, vol. 8, no. 1, 2020.

Technical Report (1.65 MB)

S. Tourani, Shekhovtsov, A., Rother, C., and Savchynskyy, B., “Taxonomy of Dual Block-Coordinate Ascent Methods for Discrete Energy Minimization”, in AISTATS 2020, 2020.

PDF (2.58 MB)

2019

K. E. Krall, Smith, A. W., Takagaki, N., and Jähne, B., “Air–sea gas exchange at wind speeds up to 85 m/s”, Ocean Science, vol. 15, p. 1783-–1799, 2019.

G. -hung Lu, Tsai, W. -ting, and Jähne, B., “Decomposing infrared images of wind waves for quantitative separation into characteristic flow processes”, IEEE Transactions on Geoscience and Remote Sensing, vol. 57, pp. 8304–8316, 2019.

A. Sanakoyeu, Tschernezki, V., Büchler, U., and Ommer, B., “Divide and Conquer the Embedding Space for Metric Learning”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2019.

2018

T. Hodaň, 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., “BOP: Benchmark for 6D object pose estimation”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2018, vol. 11214 LNCS, pp. 19–35.

A. Arnab, Zheng, S., Jayasumana, S., Romera-paredes, B., Kirillov, A., Savchynskyy, B., Rother, C., Kahl, F., and Torr, P., “Conditional Random Fields Meet Deep Neural Networks for Semantic Segmentation”, Cvpr, vol. XX, pp. 1–15, 2018.

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

2017

E. Levinkov, Uhrig, J., Tang, S., Omran, M., Insafutdinov, E., Kirillov, A., Rother, C., Brox, T., Schiele, B., and Andres, B., “Joint graph decomposition & node labeling: Problem, algorithms, applications”, in Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, 2017, vol. 2017-Janua, pp. 1904–1912.

A. Kirillov, Schlesinger, D., Zheng, S., Savchynskyy, B., Torr, P. H. S., and Rother, C., “Joint training of generic CNN-CRF models with stochastic optimization”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, vol. 10112 LNCS, pp. 221–236.

V. Ulman, Maška, M., Magnusson, K. E. G., Ronneberger, O., Haubold, C., Harder, N., Matula, P., Matula, P., Svoboda, D., Radojevic, M., Smal, I., Rohr, K., Jaldén, J., Blau, H. M., Dzyubachyk, O., Lelieveldt, B., Xiao, P., Li, Y., Cho, S. - Y., Dufour, A., Olivo-Marin, J. C., Reyes-Aldasoro, C. C., Solis-Lemus, J. A., Bensch, R., Brox, T., Stegmaier, J., Mikut, R., Wolf, S., Hamprecht, F. A., Esteves, T., Quelhas, P., Demirel, Ö., Malström, L., Jug, F., Tomančák, P., Meijering, E., Muñoz-Barrutia, A., Kozubek, M., and Ortiz-de-Solorzano, C., “An Objective Comparison of Cell Tracking Algorithms”, Nature Methods, vol. 14, no. 12, pp. 1141-1152, 2017.

Technical Report (4.24 MB)

D. Massiceti, Krull, A., Brachmann, E., Rother, C., and Torr, P. H. S., “Random Forests versus Neural Networks − What's best for camera location”. 2017.

2015

N. Krah, Testa, M., Brons, S., Jäkel, O., Parodi, K., Voss, B., and Rinaldi, I., “An advanced image processing method to improve the spatial resolution of ion radiographies”, Physics in Medicine and Biology, vol. 60, p. 8525, 2015.

S. Zheng, Prisacariu, V. Adrian, Averkiou, M., Cheng, M. Ming, Mitra, N. J., Shotton, J., Torr, P. H. S., and Rother, C., “Object proposals estimation in depth image using compact 3D shape manifolds”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, vol. 9358, pp. 196–208.

N. J. Mitra, Stam, J., Xu, K., Cheng, M. - M., Prisacariu, V. Adrian, Zheng, S., Torr, P. H. S., and Rother, C., “Pacific Graphics 2015 DenseCut: Densely Connected CRFs for Realtime GrabCut”, vol. 34, 2015.

E. - M. Didden, Thorarinsdottir, T. L., Lenkoski, A., and Schnörr, C., “Shape from Texture using Locally Scaled Point Processes”, Image Anal. Stereol., vol. 34, pp. 161-170, 2015.

D. Trofimova, “Towards Four Dimensional Visualization of Air-Water Gas Exchange”, vol. Dissertation. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ. Heidelberg, 2015.

2014

M. Takami, Bell, P., and Ommer, B., “An Approach to Large Scale Interactive Retrieval of Cultural Heritage”, in Eurographics Workshop on Graphics and Cultural Heritage, 2014.

Technical Report (7.94 MB)

B. F. Tek, Kröger, T., Mikula, S., and Hamprecht, F. A., “Automated Cell Nucleus Detection for Large-Volume Electron Microscopy of Neural Tissue”, in ISBI. Proceedings, 2014, pp. 69-72.

Technical Report (533.92 KB)

S. Zheng, Cheng, M. Ming, Warrell, J., Sturgess, P., Vineet, V., Rother, C., and Torr, P. H. S., “Dense semantic image segmentation with objects and attributes”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2014, pp. 3214–3221.

E. Eyjolfsdottir, Branson, S., Burgos-Artizzu, X. P., Hoopfer, E. D., Schor, J., Anderson, D. J., and Perona, P., “Detection of social actions in fruit flies”, Lecture Notes in Computer Science, vol. 8690, pp. 772–787, 2014.

C. Kräuter, Trofimova, D., Kiefhaber, D., Krah, N., and Jähne, B., “High resolution 2-D fluorescence imaging of the mass boundary layer thickness at free water surfaces”, J. Europ. Opt. Soc. Rap. Public., vol. 9, p. 14016, 2014.

C. Kräuter, Trofimova, D., Nagel, L., and Jähne, B., “High-resolution 2-D fluorescence imaging of gas transfer at a free water surface”, in Ocean Science Meeting, 23--28. 02. 2014, Honolulu Hawaii, 2014.

M. Hoai, Torresani, L., De La Torre, F., and Rother, C., “Learning discriminative localization from weakly labeled data”, in Pattern Recognition, 2014, vol. 47, pp. 1523–1534.

M. Takami, Bell, P., and Ommer, B., “Offline Learning of Prototypical Negatives for Efficient Online Exemplar SVM”, in Winter Conference on Applications of Computer Vision, 2014, p. 377--384.

A. Eigenstetter, Takami, M., and Ommer, B., “Randomized Max-Margin Compositions for Visual Recognition”, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2014, p. 3590--3597.

Technical Report (8.01 MB)

2013

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

F. Lenzen, Kim, K. In, Schäfer, H., Nair, R., Meister, S., Becker, F., and Garbe, C. S., “Denoising Strategies for Time-of-Flight Data”, Time-of-Flight and Depth Imaging: Sensors, Algorithms, and Applications, vol. 8200. Springer, pp. 25-45, 2013.

Technical Report (961.62 KB)

F. Lenzen, Kim, K. In, Schäfer, H., Nair, R., Meister, S., Becker, F., and Garbe, C. S., “Denoising Strategies for Time-of-Flight Data”, Time-of-Flight and Depth Imaging: Sensors, Algorithms, and Applications, vol. 8200. Springer, pp. 25-45, 2013.

Technical Report (961.62 KB)

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