| U-net: Convolutional networks for biomedical image segmentation O Ronneberger, P Fischer, T Brox International Conference on Medical image computing and computer-assisted …, 2015 | 128145 | 2015 |
| 3D U-Net: learning dense volumetric segmentation from sparse annotation Ö Çiçek, A Abdulkadir, SS Lienkamp, T Brox, O Ronneberger International conference on medical image computing and computer-assisted …, 2016 | 10372 | 2016 |
| Striving for simplicity: The all convolutional net JT Springenberg, A Dosovitskiy, T Brox, M Riedmiller arXiv preprint arXiv:1412.6806, 2014 | 6639 | 2014 |
| Flownet: Learning optical flow with convolutional networks A Dosovitskiy, P Fischer, E Ilg, C Hazirbas, V Golkov, P van der Smagt, ... 2015 IEEE International Conference on Computer Vision (ICCV), 2758-2766, 2015 | 6002* | 2015 |
| Flownet 2.0: Evolution of optical flow estimation with deep networks E Ilg, N Mayer, T Saikia, M Keuper, A Dosovitskiy, T Brox Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 4328 | 2017 |
| High accuracy optical flow estimation based on a theory for warping T Brox, A Bruhn, N Papenberg, J Weickert European conference on computer vision, 25-36, 2004 | 3961 | 2004 |
| A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation N Mayer, E Ilg, P Hausser, P Fischer, D Cremers, A Dosovitskiy, T Brox Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 3730 | 2016 |
| Discriminative unsupervised feature learning with convolutional neural networks A Dosovitskiy, JT Springenberg, M Riedmiller, T Brox Advances in neural information processing systems 27, 2014 | 2295 | 2014 |
| U-Net: deep learning for cell counting, detection, and morphometry T Falk, D Mai, R Bensch, Ö Çiçek, A Abdulkadir, Y Marrakchi, A Böhm, ... Nature methods 16 (1), 67-70, 2019 | 2247 | 2019 |
| Towards total recall in industrial anomaly detection K Roth, L Pemula, J Zepeda, B Schölkopf, T Brox, P Gehler Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 1904 | 2022 |
| Large displacement optical flow: descriptor matching in variational motion estimation T Brox, J Malik IEEE transactions on pattern analysis and machine intelligence 33 (3), 500-513, 2010 | 1882 | 2010 |
| Generating images with perceptual similarity metrics based on deep networks A Dosovitskiy, T Brox Advances in neural information processing systems 29, 2016 | 1490 | 2016 |
| Sparsity invariant cnns J Uhrig, N Schneider, L Schneider, U Franke, T Brox, A Geiger 2017 international conference on 3D Vision (3DV), 11-20, 2017 | 1154 | 2017 |
| Learning to generate chairs with convolutional neural networks A Dosovitskiy, J Tobias Springenberg, T Brox Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 1091 | 2015 |
| Object segmentation by long term analysis of point trajectories T Brox, J Malik European conference on computer vision, 282-295, 2010 | 1069 | 2010 |
| Inverting visual representations with convolutional networks A Dosovitskiy, T Brox Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 1018* | 2016 |
| Learning to estimate 3d hand pose from single rgb images C Zimmermann, T Brox Proceedings of the IEEE international conference on computer vision, 4903-4911, 2017 | 1008 | 2017 |
| U-Net: convolutional networks for biomedical image segmentation. 2015 O Ronneberger, P Fischer, T Brox arXiv preprint arXiv:1505.04597 1505, 2019 | 987 | 2019 |
| Octree generating networks: Efficient convolutional architectures for high-resolution 3d outputs M Tatarchenko, A Dosovitskiy, T Brox Proceedings of the IEEE international conference on computer vision, 2088-2096, 2017 | 957 | 2017 |
| Synthesizing the preferred inputs for neurons in neural networks via deep generator networks A Nguyen, A Dosovitskiy, J Yosinski, T Brox, J Clune Advances in neural information processing systems 29, 2016 | 953 | 2016 |
Olaf Ronnebergerapl. Prof. for Computer Science, University of Freiburg, GermanyVerified email at cs.uni-freiburg.de
