Seguir
Svetlana Lazebnik
Svetlana Lazebnik
University of Illinois at Urbana-Champaign
Dirección de correo verificada de illinois.edu - Página principal
Título
Citado por
Citado por
Año
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
108292006
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
31412012
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
26552007
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
22072015
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
15092005
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
14372018
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
12932014
Learning deep structure-preserving image-text embeddings
L Wang, Y Li, S Lazebnik
Proceedings of the IEEE conference on computer vision and pattern …, 2016
9562016
Superparsing: scalable nonparametric image parsing with superpixels
J Tighe, S Lazebnik
International Journal of Computer Vision 101, 329-349, 2013
8832013
Locality-sensitive binary codes from shift-invariant kernels
M Raginsky, S Lazebnik
NIPS 22, 1509-1517, 2009
8132009
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
7752010
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
7732018
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
7172014
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
5792006
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
5782018
Active object localization with deep reinforcement learning
JC Caicedo, S Lazebnik
Proceedings of the IEEE international conference on computer vision, 2488-2496, 2015
5782015
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
5632015
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
5532011
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
4082008
A Sparse Texture Representation Using Affine-Invariant Regions
S Lazebnik, C Schmid, J Ponce
International Conference on Computer Vision & Pattern Recognition (CVPR'03 …, 2003
3882003
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20