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Deep convolutional neural networks have been successfully applied to image classification tasks.
Video Google: A text retrieval approach to object matching in videos
J. Sivic and A. Zisserman · 2003
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Object retrieval with large vocabularies and fast spatial matching
J. Philbin, O. Chum, M. Isard, J. Sivic, and A. Zisserman · 2007
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Hamming embedding and weak geometric consistency for large scale image search
H. Jégou, M. Douze, and C. Schmid · 2008
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Lost in quantization: Improving particular object retrieval in large scale image databases
J. Philbin, O. Chum, M. Isard, J. Sivic, and A. Zisserman · 2008
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Large-scale image retrieval with compressed fisher vectors
F. Perronnin, Y. Liu, J. Sánchez, and H. Poirier · 2010
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Combining attributes and fisher vectors for efficient image retrieval
M. Douze, A. Ramisa, and C. Schmid · 2011
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Image ranking and retrieval based on multi-attribute queries
B. Siddiquie, R. S. Feris, and L. S. Davis · 2011
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Three things everyone should know to improve object retrieval
R. Arandjelović and A. Zisserman · 2012
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Negative evidences and co-occurences in image retrieval: The benefit of PCA and whitening
H. Jégou and O. Chum · 2012
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Aggregating local image descriptors into compact codes
H. Jégou, F. Perronnin, M. Douze, J. Sánchez, P. Pérez, and C. Schmid · 2012
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Whittlesearch: Image search with relative attribute feedback
A. Kovashka, D. Parikh, and K. Grauman · 2012
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ImageNet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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All about VLAD
R. Arandjelovic and A. Zisserman · 2013
Cited alongside, same era.
Revisiting the VLAD image representation
J. Delhumeau, P. H. Gosselin, H. Jégou, and P. Pérez · 2013
Cited alongside, same era.
Attribute adaptation for personalized image search
A. Kovashka and K. Grauman · 2013
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Attribute pivots for guiding relevance feedback in image search
A. Kovashka and K. Grauman · 2013
Cited alongside, same era.
Implied feedback: Learning nuances of user behavior in image search
D. Parikh and K. Grauman · 2013
Cited alongside, same era.
Multi-attribute queries: To merge or not to merge?
M. Rastegari, A. Diba, D. Parikh, and A. Farhadi · 2013
Cited alongside, same era.
Triangulation embedding and democratic aggregation for image search
H. Jégou and A. Zisserman · 2014
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Caffe: Convolutional architecture for fast feature embedding
Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell · 2014
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Do convnets learn correspondence?
J. Long, N. Zhang, and T. Darrell · 2014
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Learning and transferring mid-level image representations using convolutional neural networks
M. Oquab, L. Bottou, I. Laptev, and J. Sivic · 2014
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Cnn features off-the-shelf: an astounding baseline for recognition
A. S. Razavian, H. Azizpour, J. Sullivan, and S. Carlsson · 2014
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P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, R. Fergus, and Y. LeCun · 2013
Cited alongside, same era.
Oriented pooling for dense and non-dense rotation-invariant features
W. Zhao, G. Gravier, and H. Jégou · 2013
Cited alongside, same era.
Neural codes for image retrieval
A. Babenko, A. Slesarev, A. Chigorin, and V. Lempitsky · 2014
Cited alongside, same era.
In search of art
E. J. Crowley and A. Zisserman · 2014
Cited alongside, same era.
DeCAF: A deep convolutional activation feature for generic visual recognition
J. Donahue, Y. Jia, O. Vinyals, J. Hoffman, N. Zhang, E. Tzeng, and T. Darrell · 2014
Cited alongside, same era.
Multi-scale orderless pooling of deep convolutional activation features
Y. Gong, L. Wang, R. Guo, and S. Lazebnik · 2014
Cited alongside, same era.
A. S. Razavian, J. Sullivan, A. Maki, and S. Carlsson · 2014
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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Going deeper with convolutions
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich · 2014
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Deep learning for content-based image retrieval: A comprehensive study
J. Wan, D. Wang, S. C. H. Hoi, P. Wu, J. Zhu, Y. Zhang, and J. Li · 2014
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A discriminative CNN video representation for event detection
Z. Xu, Y. Yang, and A. G. Hauptmann · 2014
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Visualizing and understanding convolutional networks
M. D. Zeiler and R. Fergus · 2014
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