Publications

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2021
A. Blattmann, Milbich, T., Dorkenwald, M., and Ommer, B., Behavior-Driven Synthesis of Human Dynamics, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2021.
T. Milbich, Roth, K., Sinha, S., Schmidt, L., Ghassemi, M., and Ommer, B., Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning. 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.
L. M. Schütz, Louveaux, M., Vilches-Barro, A., Bouziri, S., Cerrone, L., Wolny, A., Kreshuk, A., Hamprecht, F. A., and Maizel, A., Integration of Cell Growth and Asymmetric Division during Lateral Root Initiation in Arabidopsis thaliana, Plant and Cell Physiology, vol. 62, no. 8, pp. 1269-1279, 2021.
A. Blattmann, Milbich, T., Dorkenwald, M., and Ommer, B., iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis, in Proceedings of the International Conference on Computer Vision (ICCV), 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.
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.
K. Roth, Milbich, T., Ommer, B., Cohen, J. Paul, and Ghassemi, M., S2SD: Simultaneous Similarity-based Self-Distillation for Deep Metric Learning, Proceedings of International Conference on Machine Learning (ICML). 2021.
M. Dorkenwald, Milbich, T., Blattmann, A., Rombach, R., Derpanis, K. G., and Ommer, B., Stochastic Image-to-Video Synthesis usin cINNs, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2021.
A. Blattmann, Milbich, T., Dorkenwald, M., and Ommer, B., Understanding Object Dynamics for Interactive Image-to-Video Synthesis, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 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. T. Radev, Mertens, U. K., Voss, A., Ardizzone, L., and Köthe, U., BayesFlow: Learning complex stochastic models with invertible neural networks, 2020.PDF icon PDF (5.36 MB)
T. Dencker, Klinkisch, P., Maul, S. M., and Ommer, B., Deep learning of cuneiform sign detection with weak supervision using transliteration alignment, PLoS ONE, vol. 15, no. 12, 2020.
T. Milbich, Roth, K., Bharadhwaj, H., Sinha, S., Bengio, Y., Ommer, B., and Cohen, J. Paul, DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning, IEEE European Conference on Computer Vision (ECCV). 2020.
L. Ardizzone, Mackowiak, R., Rother, C., and Köthe, U., Exact Information Bottleneck with Invertible Neural Networks: Getting the Best of Discriminative and Generative Modeling, 2020.PDF icon PDF (2.87 MB)
T. Milbich, Roth, K., and Ommer, B., PADS: Policy-Adapted Sampling for Visual Similarity Learning, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020, vol. 1, no. 1.
K. Roth, Milbich, T., Sinha, S., Gupta, P., Ommer, B., and Cohen, J. Paul, Revisiting Training Strategies and Generalization Performance in Deep Metric Learning, International Conference on Machine Learning (ICML). 2020.
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 icon PDF (8.77 MB)
T. Milbich, Roth, K., Brattoli, B., and Ommer, B., Sharing Matters for Generalization in Deep Metric Learning, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020.
T. Milbich, Ghori, O., and Ommer, B., Unsupervised Representation Learning by Discovering Reliable Image Relations, Pattern Recognition, vol. 102, 2020.
B. Jähne, What controls air-sea gas exchange at extreme wind speeds? Evidence from laboratory experiments, Recent Advances in the Study of Oceanic Whitecaps. Springer, pp. 133–150, 2020.
2019
J. Kleesiek, Morshuis, J. Nikolas, Isensee, F., Deike-Hofmann, K., Paech, D., Kickingereder, P., Köthe, U., Rother, C., Forsting, M., Wick, W., Bendszus, M., Schlemmer, H. Peter, and Radbruch, A., Can Virtual Contrast Enhancement in Brain MRI Replace Gadolinium?: A Feasibility Study, Investigative Radiology, vol. 54, pp. 653–660, 2019.
R. Mackowiak, Lenz, P., Ghori, O., Diego, F., Lange, O., and Rother, C., CEREALS - Cost-Effective REgion-based Active Learning for Semantic Segmentation, in British Machine Vision Conference 2018, BMVC 2018, 2019.
A. Imle, Kumberger, P., Schnellbächer, N. D., Fehr, J., Carillo-Bustamente, P., Ales, J., Schmidt, P., Ritter, C., Godinez, W. J., Müller, B., Rohr, K., Hamprecht, F. A., Schwarz, U. S., Graw, F., and Fackler, O. T., Experimental and computational analyses reveal that environmental restrictions shape HIV-1 spread in 3D cultures, Nature Communications, vol. 13;10(1), 2019.
H. Abu Alhaija, Mustikovela, S. Karthik, Geiger, A., and Rother, C., Geometric Image Synthesis, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019, vol. 11366 LNCS, pp. 85–100.
O. Hosseini Jafari, Mustikovela, S. Karthik, Pertsch, K., Brachmann, E., and Rother, C., iPose: Instance-Aware 6D Pose Estimation of Partly Occluded Objects, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019, vol. 11363 LNCS, pp. 477–492.
T. Leistner, Schilling, H., Mackowiak, R., Gumhold, S., and Rother, C., Learning to Think Outside the Box: Wide-Baseline Light Field Depth Estimation with EPI-Shift, in Proceedings - 2019 International Conference on 3D Vision, 3DV 2019, 2019, pp. 249–257.PDF icon PDF (8.94 MB)
T. J. Adler, Ayala, L., Ardizzone, L., Kenngott, H. G., Vemuri, A., Müller-Stich, B. P., Rother, C., Köthe, U., and Maier-Hein, L., Out of Distribution Detection for Intra-operative Functional Imaging, in MICCAI UNSURE Workshop 2019, 2019, vol. 11840 LNCS, pp. 75–82.PDF icon PDF (3.1 MB)
T. J. Adler, Ayala, L., Ardizzone, L., Kenngott, H. G., Vemuri, A., Müller-Stich, B. P., Rother, C., Köthe, U., and Maier-Hein, L., Out of Distribution Detection for Intra-operative Functional Imaging, in MICCAI UNSURE Workshop 2019, 2019, vol. 11840 LNCS, pp. 75–82.PDF icon PDF (3.1 MB)
D. Lorenz, Bereska, L., Milbich, T., and Ommer, B., Unsupervised Part-Based Disentangling of Object Shape and Appearance, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (Oral + Best paper finalist: top 45 / 5160 submissions), 2019.
D. Kotovenko, Sanakoyeu, A., Lang, S., Ma, P., and Ommer, B., Using a Transformation Content Block For Image Style Transfer, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2019.

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