| Three things everyone should know to improve object retrieval R Arandjelovic, A Zisserman Computer Vision and Pattern Recognition (CVPR), IEEE Conference on, 2012 | 1314 | 2012 |
| NetVLAD: CNN architecture for weakly supervised place recognition R Arandjelović, P Gronat, A Torii, T Pajdla, J Sivic Computer Vision and Pattern Recognition (CVPR), IEEE Conference on, 2016 | 1254 | 2016 |
| All about VLAD R Arandjelovic, A Zisserman Computer Vision and Pattern Recognition (CVPR), IEEE Conference on, 2013 | 697 | 2013 |
| Look, Listen and Learn R Arandjelović, A Zisserman Computer Vision (ICCV), 2011 IEEE International Conference on, 2017 | 338* | 2017 |
| 24/7 place recognition by view synthesis A Torii, R Arandjelovic, J Sivic, M Okutomi, T Pajdla Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015 | 267 | 2015 |
| Convolutional neural network architecture for geometric matching I Rocco, R Arandjelović, J Sivic Computer Vision and Pattern Recognition (CVPR), IEEE Conference on, 2017 | 243 | 2017 |
| Objects that sound R Arandjelović, A Zisserman European conference on computer vision (ECCV), 2017 | 192* | 2017 |
| On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models S Gowal, K Dvijotham, R Stanforth, R Bunel, C Qin, J Uesato, ... NIPS 2018 workshop on Security in Machine Learning, 2018 | 147 | 2018 |
| Multiple queries for large scale specific object retrieval R Arandjelovic, A Zisserman Proceedings of the British Machine Vision Conference (BMVC), 2012 | 128 | 2012 |
| DisLocation: Scalable descriptor distinctiveness for location recognition R Arandjelović, A Zisserman Asian Conference on Computer Vision, 188-204, 2014 | 115 | 2014 |
| Smooth object retrieval using a bag of boundaries R Arandjelovic, A Zisserman Computer Vision (ICCV), 2011 IEEE International Conference on, 375-382, 2011 | 101 | 2011 |
| Neighbourhood Consensus Networks I Rocco, M Cimpoi, R Arandjelović, A Torii, T Pajdla, J Sivic Neural Information Processing Systems (NIPS), 2018 | 92 | 2018 |
| Training verified learners with learned verifiers K Dvijotham, S Gowal, R Stanforth, R Arandjelovic, B O'Donoghue, ... arXiv preprint arXiv:1805.10265, 2018 | 90 | 2018 |
| End-to-end weakly-supervised semantic alignment I Rocco, R Arandjelovic, J Sivic Computer Vision and Pattern Recognition (CVPR), IEEE Conference on, 2018 | 88 | 2018 |
| AXES at TRECVid 2011 K McGuinness, R Aly, S Chen, M Frappier, K Martijn, H Lee, R Ordelman, ... | 70* | 2011 |
| On-the-fly learning for visual search of large-scale image and video datasets K Chatfield, R Arandjelović, O Parkhi, A Zisserman International journal of multimedia information retrieval 4 (2), 75-93, 2015 | 54 | 2015 |
| Sketch recognition by fusion of temporal and image-based features R Arandjelović, TM Sezgin Pattern Recognition 44 (6), 1225-1234, 2011 | 44 | 2011 |
| Visual vocabulary with a semantic twist R Arandjelović, A Zisserman Asian Conference on Computer Vision, 178-195, 2014 | 42 | 2014 |
| GhostVLAD for set-based face recognition Y Zhong, R Arandjelović, A Zisserman Asian Conference on Computer Vision, 2018 | 40 | 2018 |
| Efficient image retrieval for 3D structures R Arandjelovic, A Zisserman Proceedings of the British Machine Vision Conference (BMVC), 30.1-30.11, 2010 | 34 | 2010 |
Andrew ZissermanUniversity of OxfordEmail verificata su robots.ox.ac.uk
