| 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 | 171 | 2018 |
| 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 | 114 | 2019 |
| CliqueCNN: Deep Unsupervised Exemplar Learning MA Bautista, A Sanakoyeu, E Sutter, B Ommer Advances In Neural Information Processing Systems, 3846-3854, 2016 | 110 | 2016 |
| 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 | 105 | 2019 |
| Semi-Supervised Segmentation of Salt Bodies in Seismic Images using an Ensemble of Convolutional Neural Networks Y Babakhin, A Sanakoyeu, H Kitamura German Conference on Pattern Recognition (GCPR), 218-231, 2019 | 59* | 2019 |
| 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 | 56 | 2019 |
| Transferring dense pose to proximal animal classes A Sanakoyeu, V Khalidov, MS McCarthy, A Vedaldi, N Neverova Proceedings of the IEEE/CVF Conference on computer vision and pattern …, 2020 | 46 | 2020 |
| Deep unsupervised learning of visual similarities A Sanakoyeu, MA Bautista, B Ommer Pattern Recognition 78, 331-343, 2018 | 34 | 2018 |
| Deep unsupervised similarity learning using partially ordered sets MA Bautista, A Sanakoyeu, B Ommer Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 34 | 2017 |
| Improving deep metric learning by divide and conquer A Sanakoyeu, P Ma, V Tschernezki, B Ommer IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (11), 8306 …, 2021 | 9 | 2021 |
| Discovering relationships between object categories via universal canonical maps N Neverova, A Sanakoyeu, P Labatut, D Novotny, A Vedaldi Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 9 | 2021 |
| MotionCNN: a strong baseline for motion prediction in autonomous driving S Konev, K Brodt, A Sanakoyeu arXiv preprint arXiv:2206.02163, 2022 | 8 | 2022 |
| Self-supervised depth denoising using lower-and higher-quality RGB-d sensors A Shabanov, I Krotov, N Chinaev, V Poletaev, S Kozlukov, I Pasechnik, ... 2020 International Conference on 3D Vision (3DV), 743-752, 2020 | 3 | 2020 |
| VisCo Grids: Surface Reconstruction with Viscosity and Coarea Grids A Pumarola, A Sanakoyeu, L Yariv, A Thabet, Y Lipman Advances in Neural Information Processing Systems, 0 | | |
Björn OmmerProfessor, Computer Vision & Learning Group (CompVis), University of MunichDirección de correo verificada de uni-heidelberg.de
