| 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 | 5088 | 2014 |
| Deep face recognition OM Parkhi, A Vedaldi, A Zisserman British Machine Vision Association, 2015 | 4980 | 2015 |
| 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 | 3886* | 2010 |
| 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 | 3676 | 2014 |
| Matconvnet: Convolutional neural networks for matlab A Vedaldi, K Lenc Proceedings of the 23rd ACM international conference on Multimedia, 689-692, 2015 | 3225 | 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 | 2909 | 2016 |
| Instance normalization: The missing ingredient for fast stylization D Ulyanov, A Vedaldi, V Lempitsky arXiv preprint arXiv:1607.08022, 2016 | 2367 | 2016 |
| Deep image prior D Ulyanov, A Vedaldi, V Lempitsky Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 1737* | 2018 |
| Understanding deep image representations by inverting them A Mahendran, A Vedaldi Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 1731 | 2015 |
| Speeding up Convolutional Neural Networks with Low Rank Expansions M Jaderberg, A Vedaldi, A Zisserman British Machine Vision Conference (BMVC), 2014 | 1398 | 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 | 1342 | 2017 |
| Efficient additive kernels via explicit feature maps A Vedaldi, A Zisserman IEEE transactions on pattern analysis and machine intelligence 34 (3), 480-492, 2012 | 1301 | 2012 |
| The devil is in the details: an evaluation of recent feature encoding methods K Chatfield, V Lempitsky, A Vedaldi, A Zisserman BMVC, 2011 | 1156 | 2011 |
| 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 | 1096 | 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), 1-20, 2016 | 1062 | 2016 |
| Interpretable explanations of black boxes by meaningful perturbation RC Fong, A Vedaldi Proceedings of the IEEE international conference on computer vision, 3429-3437, 2017 | 1043 | 2017 |
| 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 | 1032 | 2014 |
| Multiple kernels for object detection A Vedaldi, V Gulshan, M Varma, A Zisserman 2009 IEEE 12th international conference on computer vision, 606-613, 2009 | 1002 | 2009 |
| Deep filter banks for texture recognition and segmentation M Cimpoi, S Maji, A Vedaldi Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 983 | 2015 |
| Quick shift and kernel methods for mode seeking A Vedaldi, S Soatto European conference on computer vision, 705-718, 2008 | 963 | 2008 |
Andrew ZissermanUniversity of OxfordVerified email at robots.ox.ac.uk
