| Domain-adversarial training of neural networks Y Ganin, E Ustinova, H Ajakan, P Germain, H Larochelle, F Laviolette, ... Journal of machine learning research 17 (59), 1-35, 2016 | 9403 | 2016 |
| Unsupervised domain adaptation by backpropagation Y Ganin, V Lempitsky International Conference on Machine Learning (ICML 2015), 2015 | 6873 | 2015 |
| Instance normalization: The missing ingredient for fast stylization D Ulyanov, A Vedaldi, V Lempitsky arXiv preprint arXiv:1607.08022, 2016 | 4268 | 2016 |
| Deep image prior D Ulyanov, A Vedaldi, V Lempitsky Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 3517* | 2018 |
| The devil is in the details: an evaluation of recent feature encoding methods. K Chatfield, VS Lempitsky, A Vedaldi, A Zisserman BMVC 2 (4), 8, 2011 | 2337 | 2011 |
| Neural codes for image retrieval A Babenko, A Slesarev, A Chigorin, V Lempitsky Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014 | 1513 | 2014 |
| Learning to count objects in images V Lempitsky, A Zisserman Advances in neural information processing systems 23, 2010 | 1469 | 2010 |
| Escape from cells: Deep kd-networks for the recognition of 3d point cloud models R Klokov, V Lempitsky Proceedings of the IEEE international conference on computer vision, 863-872, 2017 | 1181 | 2017 |
| Aggregating local deep features for image retrieval A Babenko, V Lempitsky Proceedings of the IEEE international conference on computer vision, 1269-1277, 2015 | 1147* | 2015 |
| Texture Networks: Feed-forward Synthesis of Textures and Stylized Images D Ulyanov, V Lebedev, A Vedaldi, V Lempitsky International Conference on Machine Learning (ICML 2016), 2016 | 1105 | 2016 |
| Speeding-up convolutional neural networks using fine-tuned cp-decomposition V Lebedev, Y Ganin, M Rakhuba, I Oseledets, V Lempitsky arXiv preprint arXiv:1412.6553, 2014 | 1046 | 2014 |
| Improved texture networks: Maximizing quality and diversity in feed-forward stylization and texture synthesis D Ulyanov, A Vedaldi, V Lempitsky Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 908 | 2017 |
| Class-specific hough forests for object detection J Gall, V Lempitsky IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 1022 - 1029, 2009 | 840* | 2009 |
| Hough forests for object detection, tracking, and action recognition J Gall, A Yao, N Razavi, L Van Gool, V Lempitsky IEEE transactions on pattern analysis and machine intelligence 33 (11), 2188 …, 2011 | 782 | 2011 |
| Few-shot adversarial learning of realistic neural talking head models E Zakharov, A Shysheya, E Burkov, V Lempitsky Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 728 | 2019 |
| Resolution-robust large mask inpainting with fourier convolutions R Suvorov, E Logacheva, A Mashikhin, A Remizova, A Ashukha, ... Proceedings of the IEEE/CVF winter conference on applications of computer …, 2022 | 650 | 2022 |
| Optimizing binary MRFs via extended roof duality C Rother, V Kolmogorov, V Lempitsky, M Szummer 2007 IEEE conference on computer vision and pattern recognition, 1-8, 2007 | 573 | 2007 |
| Fast convnets using group-wise brain damage V Lebedev, V Lempitsky Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 548 | 2016 |
| Image segmentation with a bounding box prior V Lempitsky, P Kohli, C Rother, T Sharp 2009 IEEE 12th international conference on computer vision, 277-284, 2009 | 534 | 2009 |
| The inverted multi-index A Babenko, V Lempitsky IEEE transactions on pattern analysis and machine intelligence 37 (6), 1247-1260, 2014 | 502 | 2014 |
