| 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 | 242 | 2018 |
| 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 | 158 | 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 | 144 | 2019 |
| CliqueCNN: Deep Unsupervised Exemplar Learning MA Bautista, A Sanakoyeu, E Sutter, B Ommer Advances In Neural Information Processing Systems, 3846-3854, 2016 | 121 | 2016 |
| 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 | 89 | 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 | 80* | 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 | 57 | 2020 |
| Deep unsupervised learning of visual similarities A Sanakoyeu, MA Bautista, B Ommer Pattern Recognition 78, 331-343, 2018 | 38 | 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 |
| Avatars grow legs: Generating smooth human motion from sparse tracking inputs with diffusion model Y Du, R Kips, A Pumarola, S Starke, A Thabet, A Sanakoyeu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 33 | 2023 |
| Motioncnn: A strong baseline for motion prediction in autonomous driving S Konev, K Brodt, A Sanakoyeu arXiv preprint arXiv:2206.02163, 2022 | 30 | 2022 |
| 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 | 19 | 2021 |
| 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 | 15 | 2021 |
| Re-rend: Real-time rendering of nerfs across devices S Rojas, J Zarzar, JC Pérez, A Sanakoyeu, A Thabet, A Pumarola, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 10 | 2023 |
| 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 35, 18060-18071, 2022 | 8 | 2022 |
| Bodiffusion: Diffusing sparse observations for full-body human motion synthesis A Castillo, M Escobar, G Jeanneret, A Pumarola, P Arbeláez, A Thabet, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 6 | 2023 |
| 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 | 4 | 2020 |
| StyleAvatar: Stylizing Animatable Head Avatars JC Pérez, T Nguyen-Phuoc, C Cao, A Sanakoyeu, T Simon, P Arbeláez, ... Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024 | 1 | 2024 |
| Cache Me if You Can: Accelerating Diffusion Models through Block Caching F Wimbauer, B Wu, E Schoenfeld, X Dai, J Hou, Z He, A Sanakoyeu, ... arXiv preprint arXiv:2312.03209, 2023 | 1 | 2023 |
| Using Motion Cues to Supervise Single-Frame Body Pose and Shape Estimation in Low Data Regimes A Davydov, A Sidnev, A Sanakoyeu, Y Chen, M Salzmann, P Fua arXiv preprint arXiv:2402.02736, 2024 | | 2024 |
Björn OmmerProfessor, Computer Vision & Learning Group (CompVis), University of MunichVerified email at uni-heidelberg.de
