Publications

Show only items where

Author

Type

Term

Year

Keyword

Export 501 results:

Author Title Type [ Year

]

Filters: First Letter Of Last Name is B [Clear All Filters]

2021

D. Sitenko, Boll, B., and Schnörr, C., “Assignment Flow For Order-Constrained OCT Segmentation”, Int J Computer Vision, vol. 129, 2021.

D. Sitenko, Boll, B., and Schnörr, C., “Assignment Flows and Nonlocal PDEs on Graphs”, GCPR, in press. 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.

A. Bailoni, “Deep Learning for Graph-Based Image Instance Segmentation”. Heidelberg University, 2021.

P. Esser, Rombach, R., Blattmann, A., and Ommer, B., “ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis”. 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.

M. Afifi, Derpanis, K. G., Ommer, B., and Brown, M. S., “Learning Multi-Scale Photo Exposure Correction”, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 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.

M. Amirul Islam, Kowal, M., Esser, P., Jia, S., Ommer, B., Derpanis, K. G., and Bruce, N., “Shape or Texture: Understanding Discriminative Features in CNNs”, International Conference on Learning Representations (ICLR). 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.

M. Bellagente, Haußmann, M., Luchmann, M., and Plehn, T., “Understanding Event-Generation Networks via Uncertainties”. arXiv preprint, 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.

B. Brattoli, Büchler, U., Dorkenwald, M., Reiser, P., Filli, L., Helmchen, F., Wahl, A. - S., and Ommer, B., “Unsupervised behaviour analysis and magnification (uBAM) using deep learning”, Nature Machine Intelligence, 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.

F. Kluger, Brachmann, E., Ackermann, H., Rother, C., Yang, M. Ying, and Rosenhahn, B., “CONSAC: Robust Multi-Model Fitting by Conditional Sample Consensus”, in CVPR 2020, 2020.

PDF (9.95 MB)

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)

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

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

S. Wolf, Bailoni, A., Pape, C., Rahaman, N., Kreshuk, A., Köthe, U., and Hamprecht, F. A., “The Mutex Watershed and its Objective: Efficient, Parameter-Free Graph Partitioning”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 43, pp. 3724-3738, 2020.

Technical Report (2.58 MB)

A. Bailoni, Pape, C., Wolf, S., Kreshuk, A., and Hamprecht, F. A., “Proposal-Free Volumetric Instance Segmentation from Latent Single-Instance Masks”, GCPR, vol. 12544. Springer, pp. 331-344, 2020.

A. Bhowmik, Gumhold, S., Rother, C., and Brachmann, E., “Reinforced Feature Points: Optimizing Feature Detection and Description for a High-Level Task”, in CVPR 2020 (oral), 2020.

PDF (2.74 MB)

A. Bhowmik, Gumhold, S., Rother, C., and Brachmann, E., “Reinforced Feature Points: Optimizing Feature Detection and Description for a High-Level Task”, in CVPR 2020 (oral), 2020.

PDF (2.74 MB)

S. Wolf, Li, Y., Pape, C., Bailoni, A., Kreshuk, A., and Hamprecht, F. A., “The Semantic Mutex Watershed for Efficient Bottom-Up Semantic Instance Segmentation”, ECCV. Proceedings. pp. 208-224, 2020.

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.

M. Dorkenwald, Büchler, U., and Ommer, B., “Unsupervised Magnification of Posture Deviations Across Subjects”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2020.

article.pdf (1.15 MB)

S. Braun, Esser, P., and Ommer, B., “Unsupervised Part Discovery by Unsupervised Disentanglement”, Proceedings of the German Conference on Pattern Recognition (GCPR) (Oral). Tübingen, 2020.

2019

B. Jähne, “Air-Sea Gas Exchange”, Encyclopedia of Ocean Sciences, vol. 6. Academic Press, pp. 1–13, 2019.

A. L. Bendinger, Debus, C., Glowa, C., Karger, C. P., Peter, J., and Storath, M., “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, vol. 64, no. 4, 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.

Publications

Pages