| 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 | 8686 | 2014 |
| Deep face recognition O Parkhi, A Vedaldi, A Zisserman BMVC 2015-Proceedings of the British Machine Vision Conference 2015, 2015 | 6618 | 2015 |
| Fully-convolutional siamese networks for object tracking L Bertinetto, J Valmadre, JF Henriques, A Vedaldi, PHS Torr Computer Vision–ECCV 2016 Workshops: Amsterdam, The Netherlands, October 8 …, 2016 | 5011 | 2016 |
| Instance normalization: The missing ingredient for fast stylization D Ulyanov arXiv preprint arXiv:1607.08022, 2016 | 4458 | 2016 |
| 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 | 4325 | 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 | 4076* | 2010 |
| Deep image prior D Ulyanov, A Vedaldi, V Lempitsky Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 3715* | 2018 |
| Matconvnet: Convolutional neural networks for matlab A Vedaldi, K Lenc Proceedings of the 23rd ACM international conference on Multimedia, 689-692, 2015 | 3537 | 2015 |
| 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 | 2731 | 2014 |
| Understanding deep image representations by inverting them A Mahendran, A Vedaldi Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 2351 | 2015 |
| The devil is in the details: an evaluation of recent feature encoding methods K Chatfield, V Lempitsky, A Vedaldi, A Zisserman BMVC, 2011 | 2341 | 2011 |
| Fine-grained visual classification of aircraft S Maji, E Rahtu, J Kannala, M Blaschko, A Vedaldi arXiv preprint arXiv:1306.5151, 2013 | 2209 | 2013 |
| Cats and dogs OM Parkhi, A Vedaldi, A Zisserman, CV Jawahar Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on …, 2012 | 1932 | 2012 |
| 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 | 1842 | 2017 |
| Interpretable explanations of black boxes by meaningful perturbation RC Fong, A Vedaldi Proceedings of the IEEE international conference on computer vision, 3429-3437, 2017 | 1836 | 2017 |
| Speeding up Convolutional Neural Networks with Low Rank Expansions M Jaderberg, A Vedaldi, A Zisserman British Machine Vision Conference (BMVC), 2014 | 1820 | 2014 |
| 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 | 1780 | 2016 |
| Reading text in the wild with convolutional neural networks M Jaderberg, K Simonyan, A Vedaldi, A Zisserman International journal of computer vision 116, 1-20, 2016 | 1402 | 2016 |
| Explainable AI: interpreting, explaining and visualizing deep learning W Samek, G Montavon, A Vedaldi, LK Hansen, KR Müller Springer Nature, 2019 | 1326 | 2019 |
| Efficient additive kernels via explicit feature maps A Vedaldi, A Zisserman IEEE transactions on pattern analysis and machine intelligence 34 (3), 480-492, 2012 | 1305 | 2012 |
Andrew ZissermanUniversity of OxfordVerified email at robots.ox.ac.uk
