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Recent results indicate that the generic descriptors extracted from the convolutional neural networks are very powerful.
Scalable recognition with a vocabulary tree
D. Nistér and H. Stewénius · 2006
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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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Automated flower classification over a large number of classes
M.-E. Nilsback and A. Zisserman · 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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Describing objects by their attributes
A. Farhadi, I. Endres, D. Hoiem, and D. A. Forsyth · 2009
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Recognizing indoor scenes
A. Quattoni and A. Torralba · 2009
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Object bank: A high-level image representation for scene classification & semantic feature sparsification
L.-J. Li, H. Su, E. P. Xing, and F.-F. Li · 2010
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Learning a fine vocabulary
A. Mikulík, M. Perdoch, O. Chum, and J. Matas · 2010
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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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Sparse representations and distance learning for attribute based category recognition
G. Tsagkatakis and A. E. Savakis · 2010
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A discriminative latent model of object classes and attributes
Y. Wang and G. Mori · 2010
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Smooth object retrieval using a bag of boundaries
R. Arandjelović and A. Zisserman · 2011
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Describing people: A poselet-based approach to attribute classification
L. D. Bourdev, S. Maji, and J. Malik · 2011
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Bicos: A bi-level co-segmentation method for image classification
Y. Chai, V. S. Lempitsky, and A. Zisserman · 2011
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Asymmetric hamming embedding: taking the best of our bits for large scale image search
M. Jain, H. Jégou, and P. Gros · 2011
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Scene recognition and weakly supervised object localization with deformable part-based models
M. Pandey and S. Lazebnik · 2011
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Contextualizing object detection and classification
Z. Song, Q. Chen, Z. Huang, Y. Hua, and S. Yan · 2011
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The Caltech-UCSD Birds-200-2011 Dataset
C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie · 2011
Cited alongside, same era.
Combining randomization and discrimination for fine-grained image categorization
B. Yao, A. Khosla, and F.-F. Li · 2011
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Hierarchical matching with side information for image classification
Q. Chen, Z. Song, Y. Hua, Z. Huang, and S. Yan · 2012
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The PASCAL Visual Object Classes Challenge 2012 (VOC2012) Results
M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman · 2012
Cited alongside, same era.
Negative evidences and co-occurences in image retrieval: The benefit of pca and whitening
H. Jégou and O. Chum · 2012
Cited alongside, same era.
Aggregating local image descriptors into compact codes
H. Jégou, F. Perronnin, M. Douze, J. Sánchez, P. Pérez, and C. Schmid · 2012
Rich feature hierarchies for accurate object detection and semantic segmentation
R. B. Girshick, J. Donahue, T. Darrell, and J. Malik · 2013
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Blocks that shout: Distinctive parts for scene classification
M. Juneja, A. Vedaldi, C. V. Jawahar, and A. Zisserman · 2013
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Harvesting mid-level visual concepts from large-scale internet images
Q. Li, J. Wu, and Z. Tu · 2013
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Learning and transferring mid-level image representations using convolutional neural networks
M. Oquab, L. Bottou, I. Laptev, and J. Sivic · 2013
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Learning discriminative part detectors for image classification and cosegmentation
J. Sun and J. Ponce · 2013
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Cited alongside, same era.
Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
Cited alongside, same era.
Reconfigurable models for scene recognition
S. N. Parizi, J. G. Oberlin, and P. F. Felzenszwalb · 2012
Cited alongside, same era.
Cats and dogs
O. M. Parkhi, A. Vedaldi, A. Zisserman, and C. V. Jawahar · 2012
Cited alongside, same era.
A database for fine grained activity detection of cooking activities
M. Rohrbach, S. Amin, M. Andriluka, and B. Schiele · 2012
Cited alongside, same era.
Pose pooling kernels for sub-category recognition
N. Zhang, R. Farrell, and T. Darrell · 2012
Cited alongside, same era.
http://www.image-net.org/challenges/LSVRC/2013/
Imagenet large scale visual recognition challenge 2013 (ilsvrc2013) · 2013
Cited alongside, same era.
G. Tolias, Y. S. Avrithis, and H. Jégou · 2013
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Visualizing and understanding convolutional networks
M. D. Zeiler and R. Fergus · 2013
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Deformable part descriptors for fine-grained recognition and attribute prediction
N. Zhang, R. Farrell, F. Iandola, and T. Darrell · 2013
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Oriented pooling for dense and non-dense rotation-invariant features
W.-L. Zhao, H. Jégou, G. Gravier, et al · 2013
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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
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Mining mid-level features for image classification
B. Fernando, E. Fromont, and T. Tuytelaars · 2014
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Multi-scale orderless pooling of deep convolutional activation features
Y. Gong, L. Wang, R. Guo, and S. Lazebnik · 2014
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Attribute-based classification for zero-shot visual object categorization
C. H. Lampert, H. Nickisch, and S. Harmeling · 2014
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Overfeat: Integrated recognition, localization and detection using convolutional networks
P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, R. Fergus, and Y. LeCun · 2014
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Deepface: Closing the gap to human-level performance in face verification
Y. Taigman, M. Yang, M. Ranzato, and L. Wolf · 2014
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Deeppose: Human pose estimation via deep neural networks
A. Toshev and C. Szegedy · 2014
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Panda: Pose aligned networks for deep attribute modeling
N. Zhang, M. Paluri, M. Ranzato, T. Darrell, and L. Bourdev · 2014
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