| Towards end-to-end lane detection: an instance segmentation approach D Neven, B De Brabandere, S Georgoulis, M Proesmans, L Van Gool 2018 IEEE intelligent vehicles symposium (IV), 286-291, 2018 | 686 | 2018 |
| Multi-task learning for dense prediction tasks: A survey S Vandenhende, S Georgoulis, W Van Gansbeke, M Proesmans, D Dai, ... IEEE transactions on pattern analysis and machine intelligence 44 (7), 3614-3633, 2021 | 478* | 2021 |
| Disentangled person image generation L Ma, Q Sun, S Georgoulis, L Van Gool, B Schiele, M Fritz Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 471 | 2018 |
| SCAN: Learning to classify images without labels W Van Gansbeke, S Vandenhende, S Georgoulis, M Proesmans, ... Proceedings of the European Conference on Computer Vision, 2020 | 389 | 2020 |
| Unsupervised semantic segmentation by contrasting object mask proposals W Van Gansbeke, S Vandenhende, S Georgoulis, L Van Gool Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 193 | 2021 |
| Mti-net: Multi-scale task interaction networks for multi-task learning S Vandenhende, S Georgoulis, L Van Gool Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 159 | 2020 |
| Exemplar guided unsupervised image-to-image translation with semantic consistency L Ma, X Jia, S Georgoulis, T Tuytelaars, L Van Gool arXiv preprint arXiv:1805.11145, 2018 | 138 | 2018 |
| Branched Multi-Task Networks: Deciding What Layers To Share S Vandenhende, S Georgoulis, B De Brabandere, L Van Gool arXiv preprint arXiv:1904.02920, 2019 | 116 | 2019 |
| Reflectance and natural illumination from single-material specular objects using deep learning S Georgoulis, K Rematas, T Ritschel, E Gavves, M Fritz, L Van Gool, ... IEEE transactions on pattern analysis and machine intelligence 40 (8), 1932-1947, 2017 | 113* | 2017 |
| Time lens: Event-based video frame interpolation S Tulyakov, D Gehrig, S Georgoulis, J Erbach, M Gehrig, Y Li, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 91 | 2021 |
| Fast scene understanding for autonomous driving D Neven, B De Brabandere, S Georgoulis, M Proesmans, L Van Gool arXiv preprint arXiv:1708.02550, 2017 | 80 | 2017 |
| What Is Around The Camera? S Georgoulis, K Rematas, T Ritschel, M Fritz, T Tuytelaars, L Van Gool Proceedings of the IEEE International Conference on Computer Vision, 5170-5178, 2017 | 57 | 2017 |
| 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 | 50 | 2020 |
| Revisiting contrastive methods for unsupervised learning of visual representations W Van Gansbeke, S Vandenhende, S Georgoulis, LV Gool Advances in Neural Information Processing Systems 34, 16238-16250, 2021 | 43 | 2021 |
| Time lens++: Event-based frame interpolation with parametric non-linear flow and multi-scale fusion S Tulyakov, A Bochicchio, D Gehrig, S Georgoulis, Y Li, D Scaramuzza Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 37 | 2022 |
| Automated search for resource-efficient branched multi-task networks D Bruggemann, M Kanakis, S Georgoulis, L Van Gool arXiv preprint arXiv:2008.10292, 2020 | 36 | 2020 |
| Domain agnostic feature learning for image and video based face anti-spoofing S Saha, W Xu, M Kanakis, S Georgoulis, Y Chen, DP Paudel, L Van Gool Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 35 | 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 | 33 | 2021 |
| Learning to relate depth and semantics for unsupervised domain adaptation S Saha, A Obukhov, DP Paudel, M Kanakis, Y Chen, S Georgoulis, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 32 | 2021 |
| T-basis: a compact representation for neural networks A Obukhov, M Rakhuba, S Georgoulis, M Kanakis, D Dai, L Van Gool International Conference on Machine Learning, 7392-7404, 2020 | 24 | 2020 |
Luc Van Goolprofessor computer vision ETH Zurich,KU Leuven,INSAIT,Head Toyota Lab TRACE @KULÐBestätigte E-Mail-Adresse bei ethz.ch
