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We present an approach to matching images of objects in fine-grained datasets without using part annotations, with an application to the challenging problem of weakly supervised single-view reconstruction.
Shape matching and object recognition using shape contexts
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Distinctive image features from scale-invariant keypoints
D. G. Lowe · 2004
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Learning a similarity metric discriminatively, with application to face verification
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Modeling the world from Internet photo collections
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Skeletal graphs for efficient structure from motion
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S. Winder, G. Hua, and M. Brown · 2009
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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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Articulated pose estimation with flexible mixtures-of-parts
Y. Yang and D. Ramanan · 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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Dense object reconstruction with semantic priors
S. Y.-Z. Bao, M. Chandraker, Y. Lin, and S. Savarese · 2013
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Localizing parts of faces using a consensus of exemplars
P. N. Belhumeur, D. W. Jacobs, D. J. Kriegman, and N. Kumar · 2013
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How do you tell a blackbird from a crow?
T. Berg and P. N. Belhumeur · 2013
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T. J. Cashman and A. W. Fitzgibbon · 2013
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Deformable spatial pyramid matching for fast dense correspondences
J. Kim, C. Liu, F. Sha, and K. Grauman · 2013
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Discriminative unsupervised feature learning with convolutional neural networks
A.Dosovitskiy, J.T.Springenberg, M.Riedmiller, and T.Brox · 2014
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Virtual view networks for object reconstruction
J. Carreira, A. Kar, S. Tulsiani, and J. Malik · 2015
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Semantic image segmentation with deep convolutional nets and fully connected crfs
L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille · 2015
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Flownet: Learning optical flow with convolutional networks
P. Fischer, A. Dosovitskiy, E. Ilg, P. Häusser, C. Hazırbaş, V. Golkov, P. van der Smagt, D. Cremers, and T. Brox · 2015
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Matchnet: Unifying feature and metric learning for patch-based matching
X. Han, T. Leung, Y. Jia, R. Sukthankar, and A. C. Berg · 2015
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Spatial transformer networks
M. Jaderberg, K. Simonyan, A. Zisserman, and K. Kavukcuoglu · 2015
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Category-specific object reconstruction from a single image
A. Kar, S. Tulsiani, J. Carreira, and J. Malik · 2015
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Do convnets learn correspondence?
J. L. Long, N. Zhang, and T. Darrell · 2014
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Joint training of a convolutional network and a graphical model for human pose estimation
J. J. Tompson, A. Jain, Y. LeCun, and C. Bregler · 2014
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Reconstructing PASCAL VOC
S. Vicente, J. Carreira, L. de Agapito, and J. Batista · 2014
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Learning to see by moving
P. Agrawal, J. Carreira, and J. Malik · 2015
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Fine-grained recognition without part annotations
J. Krause, H. Jin, J. Yang, and F.-F. Li · 2015
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The birds of north america online (p. rodewald, ed.)
C. L. of Ornithology · 2015
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Viewpoints and keypoints
S. Tulsiani and J. Malik · 2015
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Learning to compare image patches via convolutional neural networks
S. Zagoruyko and N. Komodakis · 2015
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Flowweb: Joint image set alignment by weaving consistent, pixel-wise correspondences
T. Zhou, Y. J. Lee, S. X. Yu, and A. A. Efros · 2015
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