Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories S Lazebnik, C Schmid, J Ponce 2006 IEEE computer society conference on computer vision and pattern …, 2006 | 10723 | 2006 |
Iterative quantization: A procrustean approach to learning binary codes for large-scale image retrieval Y Gong, S Lazebnik, A Gordo, F Perronnin IEEE transactions on pattern analysis and machine intelligence 35 (12), 2916 …, 2012 | 3079 | 2012 |
Local features and kernels for classification of texture and object categories: A comprehensive study J Zhang, M Marszałek, S Lazebnik, C Schmid International journal of computer vision 73, 213-238, 2007 | 2628 | 2007 |
Flickr30k entities: Collecting region-to-phrase correspondences for richer image-to-sentence models BA Plummer, L Wang, CM Cervantes, JC Caicedo, J Hockenmaier, ... Proceedings of the IEEE international conference on computer vision, 2641-2649, 2015 | 1935 | 2015 |
A sparse texture representation using local affine regions S Lazebnik, C Schmid, J Ponce IEEE transactions on pattern analysis and machine intelligence 27 (8), 1265-1278, 2005 | 1494 | 2005 |
Multi-scale orderless pooling of deep convolutional activation features Y Gong, L Wang, R Guo, S Lazebnik Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014 | 1272 | 2014 |
Packnet: Adding multiple tasks to a single network by iterative pruning A Mallya, S Lazebnik Proceedings of the IEEE conference on Computer Vision and Pattern …, 2018 | 1245 | 2018 |
Learning deep structure-preserving image-text embeddings L Wang, Y Li, S Lazebnik Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 917 | 2016 |
Superparsing: scalable nonparametric image parsing with superpixels J Tighe, S Lazebnik International Journal of Computer Vision 101, 329-349, 2013 | 878 | 2013 |
Locality-sensitive binary codes from shift-invariant kernels M Raginsky, S Lazebnik NIPS 22, 1509-1517, 2009 | 804 | 2009 |
Building rome on a cloudless day JM Frahm, P Fite-Georgel, D Gallup, T Johnson, R Raguram, C Wu, ... Computer Vision–ECCV 2010: 11th European Conference on Computer Vision …, 2010 | 758 | 2010 |
A multi-view embedding space for modeling internet images, tags, and their semantics Y Gong, Q Ke, M Isard, S Lazebnik International journal of computer vision 106, 210-233, 2014 | 705 | 2014 |
Piggyback: Adapting a single network to multiple tasks by learning to mask weights A Mallya, D Davis, S Lazebnik Proceedings of the European conference on computer vision (ECCV), 67-82, 2018 | 702 | 2018 |
3d object modeling and recognition using local affine-invariant image descriptors and multi-view spatial constraints F Rothganger, S Lazebnik, C Schmid, J Ponce International journal of computer vision 66, 231-259, 2006 | 571 | 2006 |
Active object localization with deep reinforcement learning JC Caicedo, S Lazebnik Proceedings of the IEEE international conference on computer vision, 2488-2496, 2015 | 556 | 2015 |
Learning two-branch neural networks for image-text matching tasks L Wang, Y Li, J Huang, S Lazebnik IEEE Transactions on Pattern Analysis and Machine Intelligence 41 (2), 394-407, 2018 | 549 | 2018 |
Scene recognition and weakly supervised object localization with deformable part-based models M Pandey, S Lazebnik 2011 international conference on computer vision, 1307-1314, 2011 | 549 | 2011 |
Where to buy it: Matching street clothing photos in online shops M Hadi Kiapour, X Han, S Lazebnik, AC Berg, TL Berg Proceedings of the IEEE international conference on computer vision, 3343-3351, 2015 | 544 | 2015 |
Modeling and recognition of landmark image collections using iconic scene graphs X Li, C Wu, C Zach, S Lazebnik, JM Frahm Computer Vision–ECCV 2008: 10th European Conference on Computer Vision …, 2008 | 402 | 2008 |
A Sparse Texture Representation Using Affine-Invariant Regions S Lazebnik, C Schmid, J Ponce International Conference on Computer Vision & Pattern Recognition (CVPR'03 …, 2003 | 386 | 2003 |