| Fully-convolutional siamese networks for object tracking L Bertinetto, J Valmadre, JF Henriques, A Vedaldi, PHS Torr Proceedings of the European Conference on Computer Vision (ECCV) Workshops …, 2016 | 2013 | 2016 |
| Staple: Complementary Learners for Real-Time Tracking L Bertinetto, J Valmadre, S Golodetz, O Miksik, P Torr The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016 | 1269 | 2016 |
| End-to-end representation learning for the Correlation Filter J Valmadre, L Bertinetto, JF Henriques, A Vedaldi, PHS Torr The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 | 963* | 2017 |
| Fast online object tracking and segmentation: A unifying approach Q Wang, L Zhang, L Bertinetto, W Hu, PHS Torr Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 426 | 2019 |
| The sixth visual object tracking vot2018 challenge results M Kristan, A Leonardis, J Matas, M Felsberg, R Pflugfelder, ... Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 0-0, 2018 | 331 | 2018 |
| Learning feed-forward one-shot learners L Bertinetto, JF Henriques, J Valmadre, P Torr, A Vedaldi Advances in Neural Information Processing Systems (NeurIPS), 523-531, 2016 | 314 | 2016 |
| Meta-learning with differentiable closed-form solvers L Bertinetto, JF Henriques, PHS Torr, A Vedaldi Proceedings of the 7th International Conference on Learning Representations …, 2019 | 248 | 2019 |
| The thermal infrared visual object tracking VOT-TIR2015 challenge results M Felsberg, A Berg, G Hager, J Ahlberg, M Kristan, J Matas, A Leonardis, ... Proceedings of the ieee international conference on computer vision …, 2015 | 107 | 2015 |
| Long-term Tracking in the Wild: A Benchmark J Valmadre, L Bertinetto, JF Henriques, R Tao, A Vedaldi, A Smeulders, ... The European Conference on Computer Vision (ECCV), 2018 | 77 | 2018 |
| Anchor Diffusion for Unsupervised Video Object Segmentation Z Yang, Q Wang, L Bertinetto, W Hu, S Bai, PHS Torr The IEEE International Conference on Computer Vision (ICCV), 2019 | 39 | 2019 |
| The visual object tracking vot2015 challenge results K Matej, J Matas, A Leonardis, M Felsberg, L Čehovin, G Fernández, ... Workshop on the Visual Object Tracking Challenge (VOT, in conjunction with ICCV), 2015 | 17 | 2015 |
| Let's take this online: Adapting scene coordinate regression network predictions for online RGB-D camera relocalisation T Cavallari, L Bertinetto, J Mukhoti, P Torr, S Golodetz 2019 International Conference on 3D Vision (3DV), 564-573, 2019 | 12 | 2019 |
| Making Better Mistakes: Leveraging Class Hierarchies with Deep Networks L Bertinetto, R Mueller, K Tertikas, S Samangooei, NA Lord The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020 | 7 | 2020 |
| The Importance of Estimating Object Extent when Tracking with Correlation Filters L Bertinetto, J Valmadre, O Miksik, S Golodetz, P Torr | 7 | 2015 |
| Shot-based object retrieval from video with compressed fisher vectors L Bertinetto, A Fiandrotti, E Magli 2014 22nd European Signal Processing Conference (EUSIPCO), 2210-2214, 2014 | 2 | 2014 |
| On Episodes, Prototypical Networks, and Few-shot Learning S Laenen, L Bertinetto arXiv preprint arXiv:2012.09831, 2020 | 1 | 2020 |
| Learning (to learn) from few examples L Bertinetto University of Oxford, 2019 | | 2019 |
Philip TorrProfessor, University of OxfordVerified email at eng.ox.ac.uk
