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Part models of object categories are essential for challenging recognition tasks, where differences in categories are subtle and only reflected in appearances of small parts of the object.
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M. Zobel, A. Gebhard, D. Paulus, J. Denzler, and H. Niemann · 2000
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Object class recognition by unsupervised scale-invariant learning
R. Fergus, P. Perona, and A. Zisserman · 2003
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One-shot learning of object categories
L. Fei-Fei, R. Fergus, and P. Perona · 2006
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Composite models of objects and scenes for category recognition
D. J. Crandall and D. P. Huttenlocher · 2007
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Website of the caltech 256 dataset
G. Griffin, A. Holub, and P. Perona · 2007
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Automated flower classification over a large number of classes
M.-E. Nilsback and A. Zisserman · 2008
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Pictorial structures revisited: People detection and articulated pose estimation
M. Andriluka, S. Roth, and B. Schiele · 2009
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Poselets: Body part detectors trained using 3d human pose annotations
L. Bourdev and J. Malik · 2009
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Birdlets: Subordinate categorization using volumetric primitives and pose-normalized appearance
R. Farrell, O. Oza, N. Zhang, V. I. Morariu, T. Darrell, and L. S. Davis · 2009
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Object detection with discriminatively trained part-based models
P. F. Felzenszwalb, R. B. Girshick, D. McAllester, and D. Ramanan · 2010
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Novel dataset for fine-grained image categorization
A. Khosla, N. Jayadevaprakash, B. Yao, and L. Fei-Fei · 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. Hinton · 2012
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Cats and dogs
O. M. Parkhi, A. Vedaldi, C. V. Jawahar, and A. Zisserman · 2012
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Unsupervised template learning for fine-grained object recognition
S. Yang, L. Bo, J. Wang, and L. Shapiro · 2012
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Pose pooling kernels for sub-category recognition
N. Zhang, R. Farrell, and T. Darrell · 2012
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Efficient object detection and segmentation for fine-grained recognition
A. Angelova and S. Zhu · 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. Belhumeur · 2013
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Multipath sparse coding using hierarchical matching pursuit
L. Bo, X. Ren, and D. Fox · 2013
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Symbiotic segmentation and part localization for fine-grained categorization
Y. Chai, V. Lempitsky, and A. Zisserman · 2013
Nonparametric part transfer for fine-grained recognition
C. Göring, E. Rodner, A. Freytag, and J. Denzler · 2014
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Generalized max pooling
N. Murray and F. Perronnin · 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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Density-aware part-based object detection with positive examples
E. Riabchenko, J.-K. Kamarainen, and K. Chen · 2014
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Attention for fine-grained categorization
P. Sermanet, A. Frome, and E. Real · 2014
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Part detector discovery in deep convolutional neural networks
M. Simon, E. Rodner, and J. Denzler · 2014
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Fine-grained categorization by alignments
E. Gavves, B. Fernando, C. Snoek, A. 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
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Selective search for object recognition
J. Uijlings, K. van de Sande, T. Gevers, and A. Smeulders · 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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From generic to specific deep representations for visual recognition
H. Azizpour, A. S. Razavian, J. Sullivan, A. Maki, and S. Carlsson · 2014
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Improved bird species categorization using pose normalized deep convolutional nets
S. Branson, G. Van Horn, S. Belongie, and P. Perona · 2014
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Deep inside convolutional networks: Visualising image classification models and saliency maps
K. Simonyan, A. Vedaldi, and A. Zisserman · 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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Visualizing and understanding convolutional networks
M. D. Zeiler and R. Fergus · 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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Selective pooling vector for fine-grained recognition
G. Chen, J. Yang, H. Jin, E. Shechtman, J. Brandt, and T. Han · 2015
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Building a bird recognition app and large scale dataset with citizen scientists: The fine print in fine-grained dataset collection
G. Van Horn, S. Branson, R. Farrell, S. Haber, J. Barry, P. Ipeirotis, P. Perona, and S. Belongie · 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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