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Haußmann, M, Gerwinn, S, Look, A, Rakitsch, B and Kandemir, M (2021). Learning Partially Known Stochastic Dynamics with Empirical PAC Bayes. International Conference on Artificial Intelligence and Statistics . PMLR 130 478-486

Schiegg, M, Diego, F and Hamprecht, F A (2016). Learning Diverse Models: The Coulomb Structured Support Vector Machine. ECCV. Proceedings. Springer. LNCS 9907 585-599

Technical Report (2.54 MB)

(2000). Künstliche Intelligenz: Special Issue on Medical Computer Vision. 3

Hosseini Jafari, O, Mustikovela, S K, Pertsch, K, Brachmann, E and Rother, C (2018). iPose: Instance-Aware 6D Pose Estimation of Partly Occluded Objects. ACCV. Proceedings, in press

Technical Report (3.28 MB)

Wolf, S, Hamprecht, F A and Funke, J (2020). Inpainting Networks Learn to Separate Cells in Microscopy Images. BMCV

Technical Report (357.23 KB)

Esser, P, Rombach, R, Blattmann, A and Ommer, B (2021). ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis. https://arxiv.org/abs/2108.08827

Abu Alhaija, H, Mustikovela, S K, Geiger, A and Rother, C (2018). Geometric Image Synthesis. ACCV. Proceedings, in press

Technical Report (1.83 MB)

Haubold, C, Ales, J, Wolf, S and Hamprecht, F A (2016). A Generalized Successive Shortest Paths Solver for Tracking Dividing Targets. ECCV. Proceedings. Springer. LNCS 9911 566-582

Technical Report (1.18 MB)

von Borstel, M, Kandemir, M, Schmidt, P, Rao, M, Rajamani, K and Hamprecht, F A (2016). Gaussian process density counting from weak supervision. ECCV. Proceedings. Springer. LNCS 9905 365-380

Technical Report (1.71 MB)

Schilling, H, Diebold, M, Gutsche, M, Aziz-Ahmad, H and Jähne, B (2016). A fractal calibration pattern for improved camera calibration. Forum Bildverarbeitung. https://doi.org/10.5445/KSP/1000059899

Jenner, E, Fita, E and Hamprecht, F A (2021). Extensions of Karger's Algorithm: Why They Fail in Theory and How They Are Useful in Practice. ICCV. Proceedings. 4602-4611

Technical Report (1.1 MB)

Draxler, F, Veschgini, K, Salmhofer, M and Hamprecht, F A (2018). Essentially No Barriers in Neural Network Energy Landscape. ICML. Proceedings. 80 1308--1317

Technical Report (685.93 KB)

Hehn, T and Hamprecht, F A (2018). End-to-end Learning of Deterministic Decision Trees. German Conference on Pattern Recognition. Proceedings. Springer. LNCS 11269 612-627

Technical Report (1.4 MB)

Cerrone, L, Zeilmann, A and Hamprecht, F A (2019). End-to-End Learned Random Walker for Seeded Image Segmentation. CVPR. Proceedings. 12559-12568

Beier, T, Andres, B, Köthe, U and Hamprecht, F A (2016). An Efficient Fusion Move Algorithm for the Minimum Cost Lifted Multicut Problem. ECCV. Proceedings. Springer. LNCS 9906 715-730

Technical Report (4.89 MB)

Sanakoyeu, A, Tschernezki, V, Büchler, U and Ommer, B (2019). Divide and Conquer the Embedding Space for Metric Learning. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). https://github.com/CompVis/metric-learning-divide-and-conquer

Haubold, C, Uhlmann, V, Unser, M and Hamprecht, F A (2017). Diverse M-best Solutions by Dynamic Programming. GCPR. Proceedings. Springer. LNCS 10496 255-267

Milbich, T, Roth, K, Bharadhwaj, H, Sinha, S, Bengio, Y, Ommer, B and Cohen, J Paul (2020). DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning. IEEE European Conference on Computer Vision (ECCV). https://arxiv.org/abs/2004.13458

Esser, P, Rombach, R and Ommer, B (2020). A Disentangling Invertible Interpretation Network for Explaining Latent Representations. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). https://compvis.github.io/iin/

Article (13.07 MB)

Kirschbaum, E, Bailoni, A and Hamprecht, F A (2020). DISCo: Deep Learning, Instance Segmentation, and Correlations for Cell Segmentation in Calcium Imaging. MICCAI. Proceedings. 151-162

Fita, E, Damrich, S and Hamprecht, F A (2021). Directed Probabilistic Watershed. NeurIPS. Proceedings. 34

Technical Report (957.78 KB)

Kandemir, M and Hamprecht, F A (2015). The Deep Feed-Forward Gaussian Process: An Effective Generalization to Covariance Priors. NIPS. Proceedings. 44 145-159

Supplementary Material (223.39 KB)

Technical Report (2.58 MB)

Haußmann, M, Hamprecht, F A and Kandemir, M (2019). Deep Active Learning with Adaptive Acquisition. IJCAI. Proceedings. 2470-2476

Technical Report (137.6 KB)

Lang, S and Ommer, B (2020). Das Objekt jenseits der Digitalisierung. Das digitale Objekt. 7. http://www.deutsches-museum.de/fileadmin/Content/010_DM/060_Verlag/studies-7.pdf

lang_ommer_digitalhumanities_2020_.pdf (599.56 KB)

Peter, S, Diego, F, Hamprecht, F A and Nadler, B (2017). Cost-efficient Gradient Boosting. NIPS, poster

Kandemir, M and Hamprecht, F A (2015). Cell event detection in phase-contrast microscopy sequences from few annotations. MICCAI. Proceedings. Springer. LNCS 9351 316-323

Technical Report (564.69 KB)

Monroy, A and Ommer, B (2012). Beyond Bounding-Boxes: Learning Object Shape by Model-driven Grouping. IEEE Transactions on Pattern Analysis and Machine Intelligence. Springer. 7574 582--595

Technical Report (1.58 MB)

Blattmann, A, Milbich, T, Dorkenwald, M and Ommer, B (2021). Behavior-Driven Synthesis of Human Dynamics. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). https://arxiv.org/abs/2103.04677

Haußmann, M, Gerwinn, S and Kandemir, M (2020). Bayesian Evidential Deep Learning with PAC Regularization . 3rd Symposium on Advances in Approximate Bayesian Inference

Kandemir, M (2015). Asymmetric transfer learning with deep Gaussian processes. ICML. Proceedings. 730-738

Technical Report (570.95 KB)

Sitenko, D, Boll, B and Schnörr, C (2021). Assignment Flows and Nonlocal PDEs on Graphs. GCPR, in press

Gonzalez-Alvarado, D, Zeilmann, A and Schnörr, C (2021). Assignment Flows and Nonlocal PDEs on Graphs. GCPR, in press

Fita, E, Damrich, S and Hamprecht, F A (2022). The Algebraic Path Problem for Graph Metrics. 39th International Conference on Machine Learning, PMLR. Proceedings . 162 19178-19204

Jähne, (1995). Air-Water Gas Transfer --- Selected Papers from the Third International Symposium on Air-Water Gas Transfer. AEON. http://www.ub.uni-heidelberg.de/archiv/17063

Vianello, A, Manfredi, G, Diebold, M and Jähne, B (2016). 3D Reconstruction by a Combined Structure Tensor and Hough Transform Light-Field Approach. Forum Bildverarbeitung. https://doi.org/10.5445/KSP/1000059899

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