| 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 | 283 | 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 | 193 | 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 | 111 | 2019 |
| Rethinking style transfer: From pixels to parameterized brushstrokes D Kotovenko*, M Wright*, A Heimbrecht, B Ommer Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 84 | 2021 |
| Depthfm: Fast monocular depth estimation with flow matching M Gui, J Schusterbauer, U Prestel, P Ma, D Kotovenko, O Grebenkova, ... arXiv preprint arXiv:2403.13788, 2024 | 45 | 2024 |
| Coherentgs: Sparse novel view synthesis with coherent 3d gaussians A Paliwal, W Ye, J Xiong, D Kotovenko, R Ranjan, V Chandra, ... European Conference on Computer Vision, 19-37, 2024 | 32 | 2024 |
| Cross-image-attention for conditional embeddings in deep metric learning D Kotovenko, P Ma, T Milbich, B Ommer Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 8 | 2023 |
| Content and style disentanglement for artistic style transfer. In 2019 IEEE D Kotovenko, A Sanakoyeu, S Lang, B Ommer CVF International Conference on Computer Vision, ICCV, 4421-4430, 2019 | 8 | 2019 |
| Wast-3d: Wasserstein-2 distance for scene-to-scene stylization on 3d gaussians D Kotovenko, O Grebenkova, N Sarafianos, A Paliwal, P Ma, ... European Conference on Computer Vision, 298-314, 2024 | 2 | 2024 |
| Does VLM Classification Benefit from LLM Description Semantics? P Ma, L Rietdorf, D Kotovenko, VT Hu, B Ommer Proceedings of the AAAI Conference on Artificial Intelligence 39 (6), 5973-5981, 2025 | 1 | 2025 |
| EDGS: Eliminating Densification for Efficient Convergence of 3DGS D Kotovenko, O Grebenkova, B Ommer arXiv preprint arXiv:2504.13204, 2025 | | 2025 |
| DepthFM: Fast Generative Monocular Depth Estimation with Flow Matching M Gui, J Schusterbauer, U Prestel, P Ma, D Kotovenko, O Grebenkova, ... Proceedings of the AAAI Conference on Artificial Intelligence 39 (3), 3203-3211, 2025 | | 2025 |
| Attend to Context for Refining Embeddings in Deep Metric Learning D Kotovenko, P Ma, M Fischer, B Ommer | | |
| Cross-Image-Attention for Conditional Embeddings in Deep Metric Learning–Supplementary Material– D Kotovenko, P Ma, T Milbich, B Ommer | | |
| Bidirectional global to local attention for deep metric learning. D Kotovenko, P Ma, T Milbich, B Ommer | | |
Björn OmmerProfessor, Computer Vision & Learning Group (CompVis), University of MunichVerified email at lmu.de
