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This paper provides an extensive study on the availability of image representations based on convolutional networks (ConvNets) for the task of visual instance retrieval.
“Video google: A text retrieval approach to object matching in videos,”
Josef Sivic and Andrew Zisserman, · 2003
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“A Performance Evaluation of Local Descriptors,”
Krystian Mikolajczyk and Cordelia Schmid, · 2005
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“Scalable recognition with a vocabulary tree,”
David Nistér and Henrik Stewénius, · 2006
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“Total recall: Automatic query expansion with a generative feature model for object retrieval,”
Ondrej Chum, James Philbin, Josef Sivic, Micheal Isard, and Andrew Zisserman, · 2007
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“Object retrieval with large vocabularies and fast spatial matching,”
James Philbin, Ondrej Chum, Michael Isard, Josef Sivic, and Andrew Zisserman, · 2007
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“Fisher kernels on visual vocabularies for image categorization,”
Florent Perronnin and Christopher R. Dance, · 2007
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“Small codes and large image databases for recognition”
Antonio Torralba, Rob Fergus, and Yair Weiss, · 2008
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“Lost in quantization: Improving particular object retrieval in large scale image databases,”
James Philbin, Ondrej Chum, Michael Isard, Josef Sivic, and Andrew Zisserman, · 2008
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“Hamming embedding and weak geometric consistency for large scale image search,”
Hervé Jégou, Matthijs Douze, and Cordelia Schmid, · 2008
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“Efficient representation of local geometry for large scale object retrieval,”
Michal Perdoch, Ondrej Chum, and Jiri Matas, · 2009
Earlier work this paper cites.
“ImageNet: A Large-Scale Hierarchical Image Database,”
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei, · 2009
Earlier work this paper cites.
“Using very deep autoencoders for content-based image retrieval,”
Alex Krizhevsky and Geoffrey E. Hinton, · 2011
Earlier work this paper cites.
“Smooth object retrieval using a bag of boundaries,”
Relja Arandjelović and Andrew Zisserman, · 2011
Earlier work this paper cites.
“ImageNet classification with deep convolutional neural networks,”
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton, · 2012
Cited alongside, same era.
“Aggregating local image descriptors into compact codes,”
Hervé Jégou, Florent Perronnin, Matthijs Douze, Jorge Sánchez, Patrick Pérez, and Cordelia Schmid, · 2012
Cited alongside, same era.
“Deep inside convolutional networks: Visualising image classification models and saliency maps.,”
Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman, · 2013
Cited alongside, same era.
“To aggregate or not to aggregate: Selective match kernels for image search,”
Giorgos Tolias, Yannis S. Avrithis, and Hervé Jégou, · 2013
Cited alongside, same era.
“Oriented pooling for dense and non-dense rotation-invariant features,”
Wan-Lei Zhao, Hervé Jégou, Guillaume Gravier, et al., · 2013
Cited alongside, same era.
“Neural codes for image retrieval,”
Artem Babenko, Anton Slesarev, Alexander Chigorin, and Victor S. Lempitsky, · 2014
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“Deep learning for content-based image retrieval: A comprehensive study,”
Ji Wan, Dayong Wang, Steven Chu Hong Hoi, Pengcheng Wu, Jianke Zhu, Yongdong Zhang, and Jintao Li, · 2014
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“A Comprehensive Study Over VLAD and Product Quantization in Large-Scale Image Retrieval,”
Eleftherios Spyromitros-Xioufis, Symeon Papadopoulos, Ioannis (Yiannis) Kompatsiaris, Grigorios Tsoumakas, and Ioannis Vlahavas, · 2014
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“Multi-scale orderless pooling of deep convolutional activation features,”
Yunchao Gong, Liwei Wang, Ruiqi Guo, and Svetlana Lazebnik, · 2014
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“Learning local feature descriptors using convex optimisation,”
Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman, · 2014
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“Triangulation embedding and democratic aggregation for image search,”
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Ross B. Girshick, Forrest N. Iandola, Trevor Darrell, and Jitendra Malik, · 2014
Cited alongside, same era.
“Return of the devil in the details: Delving deep into convolutional nets,”
Ken Chatfield, Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman, · 2014
Cited alongside, same era.
“Visualizing and understanding convolutional networks,”
Matthew D. Zeiler and Rob Fergus, · 2014
Cited alongside, same era.
“Visual instance retrieval with deep convolutional networks,”
Ali S. Razavian, Josephine Sullivan, Atsuto Maki, and Stefan Carlsson, · 2014
Cited alongside, same era.
“Learning and transferring mid-level image representations using convolutional neural networks,”
Maxime Oquab, Léon Bottou, Ivan Laptev, and Josef Sivic, · 2014
Cited alongside, same era.
“Decaf: A deep convolutional activation feature for generic visual recognition,”
Jeff Donahue, Yangqing Jia, Oriol Vinyals, Judy Hoffman, Ning Zhang, Eric Tzeng, and Trevor Darrell, · 2014
Cited alongside, same era.
“Descriptor matching with convolutional neural networks: a comparison to SIFT,”
Philipp Fischer, Alexey Dosovitskiy, and Thomas Brox, · 2014
Cited alongside, same era.
Hervé Jégou and Andrew Zisserman, · 2014
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“NetVLAD: CNN architecture for weakly supervised place recognition,”
Relja Arandjelovic, Petr Gronat, Akihiko Torii, Tomas Pajdla, and Josef Sivic, · 2015
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“Exploiting local features from deep networks for image retrieval,”
Joe Yue-Hei Ng, Fan Yang, and Larry S. Davis, · 2015
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“Aggregating Local Deep Features for Image Retrieval”
Artem Babenko, and Victor Lempitsky, · 2015
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“Object detectors emerge in deep scene cnns,”
Bolei Zhou, Aditya Khosla, Àgata Lapedriza, Aude Oliva, and Antonio Torralba, · 2015
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“Very deep convolutional networks for large-scale image recognition,”
Karen Simonyan and Andrew Zisserman, · 2015
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“Factors of transferability for a generic ConvNet representation,”
Hossein Azizpour, Ali S. Razavian, Josephine Sullivan, Atsuto Maki, and Stefan Carlsson, · 2016
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“Locality in generic instance search from one example,”
Ran Tao, Efstratios Gavves, Cees G. M. Snoek, and Arnold W. M. Smeulders, · 2099
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