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Existing fine-grained visual categorization methods often suffer from three challenges: lack of training data, large number of fine-grained categories, and high intraclass vs.
Distance metric learning with application to clustering with side-information
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Neighbourhood components analysis
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Learning a similarity metric discriminatively, with application to face verification
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Dimensionality reduction by learning an invariant mapping
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J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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Distance metric learning for large margin nearest neighbor classification
K. Q. Weinberger and L. K. Saul · 2009
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Visual recognition with humans in the loop
S. Branson, C. Wah, F. Schroff, B. Babenko, P. Welinder, P. Perona, and S. Belongie · 2010
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Large scale online learning of image similarity through ranking
G. Chechik, V. Sharma, U. Shalit, and S. Bengio · 2010
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Haar random forest features and svm spatial matching kernel for stonefly species identification
N. Larios, B. Soran, L. G. Shapiro, G. Martínez-Muñoz, J. Lin, and T. G. Dietterich · 2010
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How many species of flowering plants are there?
L. N. Joppa, D. L. Roberts, and S. L. Pimm · 2011
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Novel dataset for fgvc: Stanford dogs
A. Khosla, N. Jayadevaprakash, B. Yao, and F.-F. Li · 2011
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The Caltech-UCSD Birds-200-2011 Dataset
C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie · 2011
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Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Leafsnap: A computer vision system for automatic plant species identification
N. Kumar, P. N. Belhumeur, A. Biswas, D. W. Jacobs, W. J. Kress, I. C. Lopez, and J. V. Soares · 2012
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Efficient object detection and segmentation for fine-grained recognition
A. Angelova and S. Zhu · 2013
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Efficient object detection and segmentation for fine-grained recognition
A. Angelova and S. Zhu · 2013
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Image segmentation for large-scale subcategory flower recognition
A. Angelova, S. Zhu, and Y. Lin · 2013
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Poof: Part-based one-vs.-one features for fine-grained categorization, face verification, and attribute estimation
T. Berg and P. N. Belhumeur · 2013
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Symbiotic segmentation and part localization for fine-grained categorization
Y. Chai, V. Lempitsky, and A. Zisserman · 2013
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Fine-grained categorization by alignments
E. Gavves, B. Fernando, C. G. Snoek, A. W. Smeulders, and T. Tuytelaars · 2013
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3d object representations for fine-grained categorization
J. Krause, M. Stark, J. Deng, and L. Fei-Fei · 2013
Part-based r-cnns for fine-grained category detection
N. Zhang, J. Donahue, R. Girshick, and T. Darrell · 2014
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Learning visual similarity for product design with convolutional neural networks
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Rotation-invariant convolutional neural networks for galaxy morphology prediction
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F. C. Heilbron, V. Escorcia, B. Ghanem, and J. C. Niebles · 2015
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Efficiently scaling up crowdsourced video annotation - A set of best practices for high quality, economical video labeling
C. Vondrick, D. J. Patterson, and D. Ramanan · 2013
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Improved bird species recognition using pose normalized deep convolutional nets
S. Branson, G. Van Horn, P. Perona, and S. Belongie · 2014
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A spatial-color layout feature for representing galaxy images
Y. Cui, Y. Xiang, K. Rong, R. Feris, and L. Cao · 2014
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Local alignments for fine-grained categorization
E. Gavves, B. Fernando, C. G. Snoek, A. W. Smeulders, and T. Tuytelaars · 2014
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Rich feature hierarchies for accurate object detection and semantic segmentation
R. Girshick, J. Donahue, T. Darrell, and J. Malik · 2014
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Deep metric learning using triplet network
E. Hoffer and N. Ailon · 2014
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Fine-grained recognition without part annotations
J. Krause, H. Jin, J. Yang, and L. Fei-Fei · 2015
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Simultaneous feature learning and hash coding with deep neural networks
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Learning deep representations for ground-to-aerial geolocalization
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Bilinear cnn models for fine-grained visual recognition
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Fine-grained visual categorization via multi-stage metric learning
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Construction of a large-scale image dataset using deep learning with humans in the loop
F. Yu, Y. Zhang, S. Song, A. Seff, and J. Xiao · 2015
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