| Learning multiple visual domains with residual adapters SA Rebuffi, H Bilen, A Vedaldi Conference on Neural Information Processing Systems (NeurIPS), 2017 | 1223 | 2017 |
| Weakly Supervised Deep Detection Networks H Bilen, A Vedaldi Conference on Computer Vision and Pattern Recognition (CVPR), 2016 | 1041 | 2016 |
| idlg: Improved deep leakage from gradients B Zhao, KR Mopuri, H Bilen arXiv preprint arXiv:2001.02610, 2020 | 959 | 2020 |
| Dataset condensation with gradient matching B Zhao, KR Mopuri, H Bilen arXiv preprint arXiv:2006.05929, 2020 | 759 | 2020 |
| Dynamic image networks for action recognition H Bilen, B Fernando, E Gavves, A Vedaldi, S Gould Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 743 | 2016 |
| Self-supervised video representation learning with odd-one-out networks B Fernando, H Bilen, E Gavves, S Gould Conference on Computer Vision and Pattern Recognition (CVPR), 2017 | 581 | 2017 |
| Dataset condensation with distribution matching B Zhao, H Bilen Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | 527 | 2023 |
| Efficient parametrization of multi-domain deep neural networks SA Rebuffi, H Bilen, A Vedaldi Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 509 | 2018 |
| Dataset Condensation with Differentiable Siamese Augmentation B Zhao, H Bilen International Conference on Machine Learning (ICML), 2021 | 460 | 2021 |
| Cafe: Learning to condense dataset by aligning features K Wang, B Zhao, X Peng, Z Zhu, S Yang, S Wang, G Huang, H Bilen, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 360 | 2022 |
| Action recognition with dynamic image networks H Bilen, B Fernando, E Gavves, A Vedaldi IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017 | 325 | 2017 |
| Unsupervised Learning of Object Landmarks through Conditional Image Generation T Jakab, A Gupta, H Bilen, A Vedaldi Advances in Neural Information Processing Systems (NIPS), 2018 | 324 | 2018 |
| Renderdiffusion: Image diffusion for 3d reconstruction, inpainting and generation T Anciukevičius, Z Xu, M Fisher, P Henderson, H Bilen, NJ Mitra, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 311 | 2023 |
| Weakly Supervised Object Detection with Convex Clustering H Bilen, M Pedersoli, T Tuytelaars Conference on Computer Vision and Pattern Recognition, 2015 | 266 | 2015 |
| Cross-domain Few-shot Learning with Task-specific Adapters WH Li, X Liu, H Bilen IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 | 200 | 2022 |
| Unsupervised learning of object landmarks by factorized spatial embeddings J Thewlis, H Bilen, A Vedaldi International Conference on Computer Vision (ICCV), 2017 | 189 | 2017 |
| Universal representations: The missing link between faces, text, planktons, and cat breeds H Bilen, A Vedaldi arXiv preprint arXiv:1701.07275, 2017 | 183 | 2017 |
| Weakly Supervised Object Detection with Posterior Regularization H Bilen, M Pedersoli, T Tuytelaars The British Machine Vision Conference, 2014 | 166 | 2014 |
| Universal Representation Learning from Multiple Domains for Few-shot Classification WH Li, X Liu, H Bilen International Conference on Computer Vision (ICCV), 2021 | 135 | 2021 |
| Integrated perception with recurrent multi-task neural networks H Bilen, A Vedaldi Advances in Neural Information Processing Systems, 2016 | 119 | 2016 |
Andrea VedaldiUniversity of OxfordVerified email at robots.ox.ac.uk
