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Fine-grained image recognition is a challenging computer vision problem, due to the small inter-class variations caused by highly similar subordinate categories, and the large intra-class variations in poses, scales and rotations.
GrabCut: Interactive foreground extraction using iterated graph cuts
C. Rother, V. Kolmogorov, and A. Blake · 2004
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LIBLINEAR: A library for large linear classification
R.-E. Fan, K.-W. Chang, C.-J. Hsieh, X.-R. Wang, and C.-J. Lin · 2008
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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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Object detection using strongly-supervised deformable part models
H. Azizpour and I. Laptev · 2012
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Visual recognition using embedded feature selection for curvature self-similarity
A. Eigenstetter and B. Ommer · 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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Adaptive deconvolutional networks for mid and high level feature learning
M. D. Zeiler, G. W. Taylor, and R. Fergus · 2013
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Bird species categorization using pose normalized deep convolutional nets
S. Branson, G. Van Horn, S. Belongie, and P. Perona · 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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MatConvNet: Convolutional neural networks for MATLAB
A. Vedaldi and K. Lenc · 2014
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Part-based R-CNNs for fine-grained category detection
N. Zhang, J. Donahue, R. Girshick, and T. Darrell · 2014
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Compact representation for image classification: To choose or to compress?
Y. Zhang, J. Wu, and J. Cai · 2014
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Spatial transformer networks
M. Jaderberg, K. Simonyan, A. Zisserman, and K. Kavukcuoglu · 2015
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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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Fully convolutional networks for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 2015
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Neural activation constellations: Unsupervised part model discovery with convolutional networks
M. Simon and E. Rodner · 2015
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2015
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The application of two-level attention models in deep convolutional neural network for fine-grained image classification
T. Xiao, Y. Xu, K. Yang, J. Zhang, Y. Peng, and Z. Zhang · 2015
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Part-stacked CNN for fine-grained visual categorization
S. Huang, Z. Xu, D. Tao, and Y. Zhang · 2016
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Selective convolutional descriptor aggregation for fine-grained image retrieval
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Deep LAC: Deep localization, alignment and classification for fine-grained recognition
D. Lin, X. Shen, C. Lu, and J. Jia · 2015
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Bilinear CNN models for fine-grained visual recognition
T.-Y. Lin, A. RoyChowdhury, and S. Maji · 2015
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X.-S. Wei, J.-H. Luo, and J. Wu · 2016
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Picking deep filter resonses for fine-grained image recognition
X. Zhang, H. Xiong, W. Zhou, W. Lin, and Q. Tian · 2016
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Weakly supervised fine-grained categorization with part-based image representation
Y. Zhang, X.-S. Wei, J. Wu, J. Cai, J. Lu, V.-A. Nguyen, and M. N. Do · 2016
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