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Recently, image representation built upon Convolutional Neural Network (CNN) has been shown to provide effective descriptors for image search, outperforming pre-CNN features as short-vector representations.
Programming Pearls, 2/E
Bentley, Joe · 1999
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Robust real-time object detection
Viola, Paul and Jones, Michael · 2001
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Video Google: A text retrieval approach to object matching in videos
Sivic, Josef and Zisserman, Andrew · 2003
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Distinctive image features from scale-invariant keypoints
Lowe, David · 2004
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Object retrieval with large vocabularies and fast spatial matching
Philbin, James, Chum, Ondrej, Isard, Michael, Sivic, Josef, and Zisserman, Andrew · 2007
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Lost in quantization: Improving particular object retrieval in large scale image databases
Philbin, James, Chum, Ondrej, Isard, Michael, Sivic, Josef, and Zisserman, Andrew · 2008
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Efficient algorithms for subwindow search in object detection and localization
An, Senjian, Peursum, Patrick, Liu, Wanquan, and Venkatesh, Svetha · 2009
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Integral channel features
Dollár, Piotr, Tu, Zhuowen, Perona, Pietro, and Belongie, Serge · 2009
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Detecting objects in large image collections and videos by efficient subimage retrieval
Lampert, Christoph H · 2009
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Efficient subwindow search: A branch and bound framework for object localization
Lampert, Christoph H, Blaschko, Matthew B, and Hofmann, Thomas · 2009
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Improving bag-of-features for large scale image search
Jégou, Hervé, Douze, Matthijs, and Schmid, Cordelia · 2010
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A local bag-of-features model for large-scale object retrieval
Lin, Zhe and Brandt, Jonathan · 2010
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Total recall II: Query expansion revisited
Chum, Ondrej, Mikulik, A., Perdoch, M., and Matas, J · 2011
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Hello neighbor: Accurate object retrieval with k-reciprocal nearest neighbors
Danfeng, Qin, Gammeter, S., Bossard, L., Quack, T., and Gool, L. Van · 2011
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Three things everyone should know to improve object retrieval
Arandjelovic, Relja and Zisserman, Andrew · 2012
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Approximate gaussian mixtures for large scale vocabularies
Avrithis, Yannis and Kalantidis, Yannis · 2012
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Negative evidences and co-occurences in image retrieval: The benefit of PCA and whitening
Jégou, Hervé and Chum, Ondrej · 2012
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Aggregating local descriptors into compact codes
Jégou, Hervé, Perronnin, Florent, Douze, Matthijs, Sánchez, Jorge, Pérez, Patrick, and Schmid, Cordelia · 2012
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Imagenet classification with deep convolutional neural networks
Krizhevsky, Alex, Sutskever, Ilya, and Hinton, Geoffrey E · 2012
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All about VLAD
Arandjelovic, Relja and Zisserman, Andrew · 2013
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Efficient maximum appearance search for large-scale object detection
Chen, Qiang, Song, Zheng, Feris, Rogerio, Datta, Amitava, Cao, Liangliang, Huang, Zhongyang, and Yan, Shuicheng · 2013
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Decaf: A deep convolutional activation feature for generic visual recognition
Donahue, Jeff, Jia, Yangqing, Vinyals, Oriol, Hoffman, Judy, Zhang, Ning, Tzeng, Eric, and Darrell, Trevor · 2013
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Learning vocabularies over a fine quantization
Mikulik, Andrej, Perdoch, Michal, Chum, Ondřej, and Matas, Jiří · 2013
Untangling local and global deformations in deep convolutional networks for image classification and sliding window detection
Papandreou, George, Kokkinos, Iasonas, and Savalle, Pierre-André · 2014
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Spatially-constrained similarity measure for large-scale object retrieval
Shen, Xiaohui, Lin, Zhe, Brandt, Jonathan, and Wu, Ying · 2014
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Very deep convolutional networks for large-scale image recognition
Simonyan, Karen and Zisserman, Andrew · 2014
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Locality in generic instance search from one example
Tao, Ran, Gavves, Efstratios, Snoek, Cees GM, and Smeulders, Arnold WM · 2014
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Fisher and VLAD with flair
Van de Sande, Koen EA, Snoek, Cees GM, and Smeulders, Arnold WM · 2014
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Matconvnet-convolutional neural networks for matlab
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Selective search for object recognition
Uijlings, Jasper, Van de Sande, Koen, Gevers, Theo, and Smeulders, Arnold · 2013
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Analyzing the performance of multilayer neural networks for object recognition
Agrawal, Pulkit, Girshick, Ross, and Malik, Jitendra · 2014
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Hough pyramid matching: Speeded-up geometry re-ranking for large scale image retrieval
Avrithis, Yannis and Tolias, Giorgos · 2014
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From generic to specific deep representations for visual recognition
Azizpour, Hossein, Razavian, Ali Sharif, Sullivan, Josephine, Maki, Atsuto, and Carlsson, Stefan · 2014
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Neural codes for image retrieval
Babenko, Artem, Slesarev, Anton, Chigorin, Alexandr, and Lempitsky, Victor · 2014
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Rich feature hierarchies for accurate object detection and semantic segmentation
Girshick, Ross, Donahue, Jeff, Darrell, Trevor, and Malik, Jitendra · 2014
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Vedaldi, Andrea and Lenc, Karel · 2014
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Netvlad: Cnn architecture for weakly supervised place recognition
Arandjelovic, Relja, Gronat, Petr, Torii, Akihiko, Pajdla, Tomas, and Sivic, Josef · 2015
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Aggregating deep convolutional features for image retrieval
Babenko, Artem and Lempitsky, Victor · 2015
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Fast r-cnn
Girshick, Ross · 2015
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Cross-dimensional weighting for aggregated deep convolutional features
Kalantidis, Yannis, Mellina, Clayton, and Osindero, Simon · 2015
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Multiple measurements and joint dimensionality reduction for large scale image search with short vectors
Radenović, Filip, Jegou, Herve, and Chum, Ondrej · 2015
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Faster r-cnn: Towards real-time object detection with region proposal networks
Ren, Shaoqing, He, Kaiming, Girshick, Ross, and Sun, Jian · 2015
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Discriminative part model for visual recognition
Sicre, Ronan and Jurie, Frédéric · 2015
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Image search with selective match kernels: aggregation across single and multiple images
Tolias, Giorgos, Avrithis, Yannis, and Jégou, Hervé · 2015
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Image classification and retrieval are one
Xie, Lingxi, Tian, Q, Hong, R, and Zhang, B · 2015
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Fast object retrieval using direct spatial matching
Zhong, Zhiyuan, Zhu, Jianke, and Hoi, Steven CH · 2015
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