Publications
2022
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
Garrido, Q, Damrich, S, Jäger, A, Cerletti, D, Claassen, M, Najman, L and Hamprecht, F A (2022).
Visualizing hierarchies in scRNA-seq data using a density tree-biased autoencoder.
Bioinformatics. arXiv preprint.
38 (Suppl 1) i316-i324
2021
Arlt, H, Sui, X, Folger, B, Adams, C, Chen, X, Remme, R, Hamprecht, F A, DiMaio, F, Liao, M, Goodman, J M, Farese, R V and Walther, T C (2021).
Seipin forms a flexible cage at lipid droplet formation sites. bioRxiv
Islam, M Amirul, Kowal, M, Esser, P, Jia, S, Ommer, B, Derpanis, K G and Bruce, N (2021).
Shape or Texture: Understanding Discriminative Features in CNNs.
International Conference on Learning Representations (ICLR) Dorkenwald, M, Milbich, T, Blattmann, A, Rombach, R, Derpanis, K G and Ommer, B (2021).
Stochastic Image-to-Video Synthesis usin cINNs.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Dorkenwald, M, Milbich, T, Blattmann, A, Rombach, R, Derpanis, K G and Ommer, B (2021).
Stochastic Image-to-Video Synthesis usin cINNs.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Brattoli, B, Büchler, U, Dorkenwald, M, Reiser, P, Filli, L, Helmchen, F, Wahl, A - S and Ommer, B (2021).
Unsupervised behaviour analysis and magnification (uBAM) using deep learning.
Nature Machine Intelligence.
https://rdcu.be/ch6pL 2020
Wolny, A, 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 (2020).
Accurate and Versatile 3D Segmentation of Plant Tissues at Cellular Resolution.
eLife.
9 Mustikovela, S K, Jampani, V, De Mello, S, Liu, S, Iqbal, U, Rother, C and Kautz, J (2020).
Self-Supervised Viewpoint Learning From Image Collections.
CONSAC.
https://github.com/NVlabs/SSV PDF (8.77 MB) Dorkenwald, M, Büchler, U and Ommer, B (2020).
Unsupervised Magnification of Posture Deviations Across Subjects.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) article.pdf (1.15 MB) 2019
Bendinger, A L, Debus, C, Glowa, C, Karger, C P, Peter, J and Storath, M (2019).
Bolus arrival time estimation in dynamic contrast-enhanced magnetic resonance imaging of small animals based on spline models, in press.
Physics in Medicine and Biology.
64 Kleesiek, J, 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 (2019).
Can Virtual Contrast Enhancement in Brain MRI Replace Gadolinium?: A Feasibility Study.
Investigative Radiology.
54 653–660
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 Kirschbaum, E, Haußmann, M, Wolf, S, Sonntag, H, Schneider, J, Elzoheiry, S, Kann, O, Durstewitz, D and Hamprecht, F A (2019).
LeMoNADe: Learned Motif and Neuronal Assembly Detection in calcium imaging videos.
ICLR. Proceedings Bengio, Y, Deleu, T, Rahaman, N, Ke, R, Lachapelle, S, Bilaniuk, O, Goyal, A and Pal, C (2019).
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms.
arXiv preprint arXiv:1901.10912 Technical Report (871.59 KB) Esposito, M, Hennersperger, C, Göbl, R, Demaret, L, Storath, M, Navab, N, Baust, M and Weinmann, A (2019).
Total variation regularization of pose signals with an application to 3D freehand ultrasound.
IEEE Transactions on Medical Imaging.
38(10) 2245-2258
2018
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 Ghori, O, Mackowiak, R, Bautista, M, Beuter, N, Drumond, L, Diego, F and Ommer, B (2018).
Learning to Forecast Pedestrian Intention from Pose Dynamics.
Intelligent Vehicles, IEEE, 2018 Ghori, O, Mackowiak, R, Bautista, M, Beuter, N, Drumond, L, Diego, F and Ommer, B (2018).
Learning to Forecast Pedestrian Intention from Pose Dynamics.
Intelligent Vehicles, IEEE, 2018 Pages