| Dynamic Filter Networks B De Brabandere, X Jia, T Tuytelaars, LV Gool Advances In Neural Information Processing Systems, 667-675, 2016 | 1055* | 2016 |
| 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 | 722 | 2018 |
| Semantic instance segmentation with a discriminative loss function B De Brabandere, D Neven, L Van Gool arXiv preprint arXiv:1708.02551, 2017 | 571* | 2017 |
| Instance segmentation by jointly optimizing spatial embeddings and clustering bandwidth D Neven, BD Brabandere, M Proesmans, LV Gool Proceedings of the IEEE/cvf conference on computer vision and pattern …, 2019 | 278 | 2019 |
| Sparse and noisy lidar completion with rgb guidance and uncertainty W Van Gansbeke, D Neven, B De Brabandere, L Van Gool 2019 16th international conference on machine vision applications (MVA), 1-6, 2019 | 259 | 2019 |
| Energy-efficient convnets through approximate computing B Moons, B De Brabandere, L Van Gool, M Verhelst 2016 IEEE Winter Conference on Applications of Computer Vision (WACV), 1-8, 2016 | 133 | 2016 |
| End-to-end lane detection through differentiable least-squares fitting W Van Gansbeke, B De Brabandere, D Neven, M Proesmans, L Van Gool Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 123 | 2019 |
| 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 | 122 | 2019 |
| Fast scene understanding for autonomous driving D Neven, B De Brabandere, S Georgoulis, M Proesmans, L Van Gool arXiv preprint arXiv:1708.02550, 2017 | 81 | 2017 |
| Dynamic steerable blocks in deep residual networks JH Jacobsen, B De Brabandere, AWM Smeulders arXiv preprint arXiv:1706.00598, 2017 | 28 | 2017 |
| A three-player gan: generating hard samples to improve classification networks S Vandenhende, B De Brabandere, D Neven, L Van Gool 2019 16th International Conference on Machine Vision Applications (MVA), 1-6, 2019 | 27 | 2019 |
| From Pixels to Actions: Learning to Drive a Car with Deep Neural Networks J Heylen, S Iven, B De Brabandere, J Oramas, L Van Gool, T Tuytelaars IEEE Winter Conference on Applications in Computer Vision, 2018 | 12 | 2018 |
| End-to-end lane detection through differentiable least-squares fitting BD Brabandere, WV Gansbeke, D Neven, M Proesmans, LV Gool Computer Science, 2019 | 11 | 2019 |
| Dynamic filter networks for predicting unobserved views X Jia, B De Brabandere, T Tuytelaars, L Van Gool Proceedings ECCV 2016 workshops, 1-2, 2016 | 3 | 2016 |
| Weakly-supervised semantic segmentation by learning label uncertainty R Neven, D Neven, B De Brabandere, M Proesmans, T Goedemé Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 2 | 2021 |
| System and method for generating a mask for object instances in an image W Abbeloos, D Neven, B De Brabandere, M Proesmans, L Van Gool US Patent App. 17/423,287, 2022 | 1 | 2022 |
| Method and system for processing an image and performing instance segmentation using affinity graphs H Shimizu, B De Brabandere, D Neven, M Proesmans, L Van Gool US Patent App. 17/264,164, 2021 | | 2021 |
| Object-Centric Street Scene Synthesis with Generative Adversarial Networks M Van den Abeele, D Neven, B De Brabandere, M Proesmans, ... 2020 IEEE 20th Mediterranean Electrotechnical Conference (MELECON), 665-671, 2020 | | 2020 |
| METHOD AND SYSTEM FOR LEARNING A NEURAL NETWORK TO BE USED FOR SEMANTIC INSTANCE SEGMENTATION H Shimizu, D NEVEN, B DE BRABANDERE, L Van Gool, M PROESMANS, ... | | 2019 |
| Fast Scene Understanding for Autonomous Platforms B De Brabandere | | 2019 |
Luc Van Goolprofessor computer vision ETH Zurich,KU Leuven,INSAIT,Head Toyota Lab TRACE @KULÐПотвърден имейл адрес: ethz.ch
