Svetlana Lazebnik

Affiliations: 
Computer Science University of North Carolina, Chapel Hill, Chapel Hill, NC 
Area:
Computer Science
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"Svetlana Lazebnik"
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Publications

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Wang L, Li Y, Huang J, et al. (2018) Learning Two-Branch Neural Networks for Image-Text Matching Tasks. Ieee Transactions On Pattern Analysis and Machine Intelligence
Kiapour MH, Han X, Lazebnik S, et al. (2016) Where to buy it: Matching street clothing photos in online shops Proceedings of the Ieee International Conference On Computer Vision. 11: 3343-3351
Plummer BA, Wang L, Cervantes CM, et al. (2016) Flickr30k entities: Collecting region-to-phrase correspondences for richer image-to-sentence models Proceedings of the Ieee International Conference On Computer Vision. 11: 2641-2649
Caicedo JC, Lazebnik S. (2016) Active object localization with deep reinforcement learning Proceedings of the Ieee International Conference On Computer Vision. 11: 2488-2496
Mallya A, Lazebnik S. (2016) Learning informative edge maps for indoor scene layout prediction Proceedings of the Ieee International Conference On Computer Vision. 11: 936-944
Lu Y, Javidi T, Lazebnik S. (2016) Adaptive object detection using adjacency and zoom prediction Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 2016: 2351-2359
Wang L, Li Y, Lazebnik S. (2016) Learning deep structure-preserving image-text embeddings Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 2016: 5005-5013
Tighe J, Niethammer M, Lazebnik S. (2015) Scene Parsing with Object Instance Inference Using Regions and Per-exemplar Detectors International Journal of Computer Vision. 112: 150-171
Gordo A, Perronnin F, Gong Y, et al. (2014) Asymmetric distances for binary embeddings. Ieee Transactions On Pattern Analysis and Machine Intelligence. 36: 33-47
Tighe J, Niethammer M, Lazebnik S. (2014) Scene parsing with object instances and occlusion ordering Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 3748-3755
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