| High-resolution image synthesis with latent diffusion models R Rombach, A Blattmann, D Lorenz, P Esser, B Ommer Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 2743 | 2022 |
| Taming transformers for high-resolution image synthesis P Esser, R Rombach, B Ommer Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 1109 | 2021 |
| A variational u-net for conditional appearance and shape generation P Esser, E Sutter, B Ommer Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 444 | 2018 |
| Asynchronous therapy restores motor control by rewiring of the rat corticospinal tract after stroke AS Wahl, W Omlor, JC Rubio, JL Chen, H Zheng, A Schröter, M Gullo, ... Science 344 (6189), 1250-1255, 2014 | 333 | 2014 |
| A style-aware content loss for real-time hd style transfer A Sanakoyeu, D Kotovenko, S Lang, B Ommer proceedings of the European conference on computer vision (ECCV), 698-714, 2018 | 209 | 2018 |
| Video Parsing for Abnormality Detection B Antic, B Ommer ICCV, 2011 | 183* | 2011 |
| Revisiting training strategies and generalization performance in deep metric learning K Roth, T Milbich, S Sinha, P Gupta, B Ommer, JP Cohen International Conference on Machine Learning, 8242-8252, 2020 | 151 | 2020 |
| Unsupervised part-based disentangling of object shape and appearance D Lorenz, L Bereska, T Milbich, B Ommer Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 144 | 2019 |
| Content and style disentanglement for artistic style transfer D Kotovenko, A Sanakoyeu, S Lang, B Ommer Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 137 | 2019 |
| Divide and conquer the embedding space for metric learning A Sanakoyeu, V Tschernezki, U Buchler, B Ommer Proceedings of the ieee/cvf conference on computer vision and pattern …, 2019 | 132 | 2019 |
| Improving spatiotemporal self-supervision by deep reinforcement learning U Buchler, B Brattoli, B Ommer Proceedings of the European conference on computer vision (ECCV), 770-786, 2018 | 125 | 2018 |
| Cliquecnn: Deep unsupervised exemplar learning MA Bautista, A Sanakoyeu, E Tikhoncheva, B Ommer Advances in Neural Information Processing Systems 29, 2016 | 118 | 2016 |
| Learning multi-scale photo exposure correction M Afifi, KG Derpanis, B Ommer, MS Brown Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 103 | 2021 |
| Multi-scale object detection by clustering lines B Ommer, J Malik 2009 IEEE 12th International Conference on Computer Vision, 484-491, 2009 | 103 | 2009 |
| Mic: Mining interclass characteristics for improved metric learning K Roth, B Brattoli, B Ommer Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 97 | 2019 |
| Learning the compositional nature of visual object categories for recognition B Ommer, J Buhmann IEEE Transactions on Pattern Analysis and Machine Intelligence 32 (3), 501-516, 2009 | 96 | 2009 |
| Cross and learn: Cross-modal self-supervision N Sayed, B Brattoli, B Ommer Pattern Recognition: 40th German Conference, GCPR 2018, Stuttgart, Germany …, 2019 | 91 | 2019 |
| Imagebart: Bidirectional context with multinomial diffusion for autoregressive image synthesis P Esser, R Rombach, A Blattmann, B Ommer Advances in neural information processing systems 34, 3518-3532, 2021 | 83 | 2021 |
| Deep semantic feature matching N Ufer, B Ommer Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 82 | 2017 |
| A content transformation block for image style transfer D Kotovenko, A Sanakoyeu, P Ma, S Lang, B Ommer Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 79 | 2019 |
