| Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps K Simonyan, A Vedaldi, A Zisserman Proceedings of the International Conference on Learning Representations (ICLR), 2014 | 10781 | 2014 |
| Deep face recognition O Parkhi, A Vedaldi, A Zisserman BMVC 2015-Proceedings of the British Machine Vision Conference 2015, 2015 | 7324 | 2015 |
| Fully-convolutional siamese networks for object tracking L Bertinetto, J Valmadre, JF Henriques, A Vedaldi, PHS Torr European conference on computer vision, 850-865, 2016 | 5920 | 2016 |
| Instance normalization: The missing ingredient for fast stylization D Ulyanov, A Vedaldi, V Lempitsky arXiv preprint arXiv:1607.08022, 2016 | 5292 | 2016 |
| Deep image prior D Ulyanov, A Vedaldi, V Lempitsky Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 4783* | 2018 |
| Return of the Devil in the Details: Delving Deep into Convolutional Nets K Chatfield, K Simonyan, A Vedaldi, A Zisserman British Machine Vision Conference (BMVC), 2014 | 4494 | 2014 |
| Describing textures in the wild M Cimpoi, S Maji, I Kokkinos, S Mohamed, A Vedaldi Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on,, 2014 | 4212 | 2014 |
| VLFeat: An open and portable library of computer vision algorithms A Vedaldi, B Fulkerson Proceedings of the 18th ACM international conference on Multimedia, 1469-1472, 2010 | 4146* | 2010 |
| MatConvNet: Convolutional neural networks for MATLAB A Vedaldi, K Lenc Proceedings of the 23rd ACM international conference on Multimedia, 689-692, 2015 | 3644 | 2015 |
| Fine-grained visual classification of aircraft S Maji, E Rahtu, J Kannala, M Blaschko, A Vedaldi arXiv preprint arXiv:1306.5151, 2013 | 3282 | 2013 |
| Cats and dogs OM Parkhi, A Vedaldi, A Zisserman, CV Jawahar Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on …, 2012 | 3090 | 2012 |
| Understanding deep image representations by inverting them A Mahendran, A Vedaldi Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 2623 | 2015 |
| The devil is in the details: an evaluation of recent feature encoding methods K Chatfield, V Lempitsky, A Vedaldi, A Zisserman BMVC, 2011 | 2361 | 2011 |
| Interpretable explanations of black boxes by meaningful perturbation RC Fong, A Vedaldi Proceedings of the IEEE international conference on computer vision, 3429-3437, 2017 | 2227 | 2017 |
| Synthetic data for text localisation in natural images A Gupta, A Vedaldi, A Zisserman Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 2022 | 2016 |
| Speeding up Convolutional Neural Networks with Low Rank Expansions M Jaderberg, A Vedaldi, A Zisserman British Machine Vision Conference (BMVC), 2014 | 1987 | 2014 |
| End-to-end representation learning for correlation filter based tracking J Valmadre, L Bertinetto, J Henriques, A Vedaldi, PHS Torr Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 1959 | 2017 |
| Explainable AI: interpreting, explaining and visualizing deep learning W Samek, G Montavon, A Vedaldi, LK Hansen, KR Müller Springer Nature, 2019 | 1739 | 2019 |
| Reading text in the wild with convolutional neural networks M Jaderberg, K Simonyan, A Vedaldi, A Zisserman International journal of computer vision 116 (1), 1-20, 2016 | 1495 | 2016 |
| Meta-learning with differentiable closed-form solvers L Bertinetto, JF Henriques, PHS Torr, A Vedaldi arXiv preprint arXiv:1805.08136, 2018 | 1350 | 2018 |
Andrew ZissermanUniversity of OxfordVerified email at robots.ox.ac.uk
