| Reparameterizing convolutions for incremental multi-task learning without task interference M Kanakis, D Bruggemann, S Saha, S Georgoulis, A Obukhov, ... Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 35 | 2020 |
| Automated search for resource-efficient branched multi-task networks D Bruggemann, M Kanakis, S Georgoulis, L Van Gool British Machine Vision Conference (BMVC), 2020 | 26 | 2020 |
| Exploring relational context for multi-task dense prediction D Brüggemann, M Kanakis, A Obukhov, S Georgoulis, L Van Gool Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 17 | 2021 |
| Refign: Align and refine for adaptation of semantic segmentation to adverse conditions D Brüggemann, C Sakaridis, P Truong, L Van Gool Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | 2 | 2023 |
| Composite Learning for Robust and Effective Dense Predictions M Kanakis, TE Huang, D Brüggemann, F Yu, L Van Gool Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | | 2023 |
| L2E: Lasers to Events for 6-DoF Extrinsic Calibration of Lidars and Event Cameras K Ta, D Bruggemann, T Brödermann, C Sakaridis, L Van Gool arXiv preprint arXiv:2207.01009, 2022 | | 2022 |
