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This work proposes a multi-image matching method to estimate semantic correspondences across multiple images.
Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography
M. A. Fischler and R. C. Bolles · 1981
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Determining optical flow
B. K. Horn and B. G. Schunck · 1981
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Shape and motion from image streams under orthography: a factorization method
C. Tomasi and T. Kanade · 1992
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Recovering non-rigid 3d shape from image streams
C. Bregler, A. Hertzmann, and H. Biermann · 2000
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Distinctive image features from scale-invariant keypoints
D. G. Lowe · 2004
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Shape matching and object recognition using low distortion correspondences
A. C. Berg, T. L. Berg, and J. Malik · 2005
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Histograms of oriented gradients for human detection
N. Dalal and B. Triggs · 2005
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A spectral technique for correspondence problems using pairwise constraints
M. Leordeanu and M. Hebert · 2005
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A comparison of affine region detectors
K. Mikolajczyk, T. Tuytelaars, C. Schmid, A. Zisserman, J. Matas, F. Schaffalitzky, T. Kadir, and L. Van Gool · 2005
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Surf: speeded up robust features
H. Bay, T. Tuytelaars, and L. Van Gool · 2006
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Cat head detection-how to effectively exploit shape and texture features
W. Zhang, J. Sun, and X. Tang · 2008
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Learning graph matching
T. S. Caetano, J. J. McAuley, L. Cheng, Q. V. Le, and A. J. Smola · 2009
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Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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Reweighted random walks for graph matching
M. Cho, J. Lee, and K. M. Lee · 2010
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Disambiguating visual relations using loop constraints
C. Zach, M. Klopschitz, and M. Pollefeys · 2010
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A graph-matching kernel for object categorization
O. Duchenne, A. Joulin, and J. Ponce · 2011
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Sift flow: Dense correspondence across scenes and its applications
C. Liu, J. Yuen, and A. Torralba · 2011
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An optimization approach to improving collections of shape maps
A. Nguyen, M. Ben-Chen, K. Welnicka, Y. Ye, and L. Guibas · 2011
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An optimization approach for extracting and encoding consistent maps in a shape collection
Q.-X. Huang, G.-X. Zhang, L. Gao, S.-M. Hu, A. Butscher, and L. Guibas · 2012
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Exploring collections of 3d models using fuzzy correspondences
V. G. Kim, W. Li, N. J. Mitra, S. DiVerdi, and T. A. Funkhouser · 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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Learning graphs to match
M. Cho, K. Alahari, and J. Ponce · 2013
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Structured forests for fast edge detection
P. Dollár and C. L. Zitnick · 2013
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Consistent shape maps via semidefinite programming
Q.-X. Huang and L. Guibas · 2013
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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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Multi-graph matching via affinity optimization with graduated consistency regularization
J. Yan, M. Cho, H. Zha, X. Yang, and S. Chu · 2015
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Consistency-driven alternating optimization for multigraph matching: A unified approach
J. Yan, J. Wang, H. Zha, X. Yang, and S. Chu · 2015
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A matrix decomposition perspective to multiple graph matching
J. Yan, H. Xu, H. Zha, X. Yang, H. Liu, and S. Chu · 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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Deformable spatial pyramid matching for fast dense correspondences
J. Kim, C. Liu, F. Sha, and K. Grauman · 2013
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Solving the multi-way matching problem by permutation synchronization
D. Pachauri, R. Kondor, and V. Singh · 2013
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Proximal algorithms
N. Parikh and S. Boyd · 2013
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Selective search for object recognition
J. R. Uijlings, K. E. Van De Sande, T. Gevers, and A. W. Smeulders · 2013
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Joint optimization for consistent multiple graph matching
J. Yan, Y. Tian, H. Zha, X. Yang, Y. Zhang, and S. Chu · 2013
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Near-optimal joint object matching via convex relaxation
Y. Chen, L. Guibas, and Q. Huang · 2014
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X. Zhou, M. Zhu, and K. Daniilidis · 2015
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Universal correspondence network
C. B. Choy, J. Gwak, S. Savarese, and M. Chandraker · 2016
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Warpnet: Weakly supervised matching for single-view reconstruction
A. Kanazawa, D. W. Jacobs, and M. Chandraker · 2016
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Learning covariant feature detectors
K. Lenc and A. Vedaldi · 2016
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A fast projected fixed-point algorithm for large graph matching
Y. Lu, K. Huang, and C.-L. Liu · 2016
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Deepmatching: Hierarchical deformable dense matching
J. Revaud, P. Weinzaepfel, Z. Harchaoui, and C. Schmid · 2016
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Lift: Learned invariant feature transform
K. M. Yi, E. Trulls, V. Lepetit, and P. Fua · 2016
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Learning dense correspondence via 3d-guided cycle consistency
T. Zhou, P. Krahenbuhl, M. Aubry, Q. Huang, and A. A. Efros · 2016
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Proposal flow: Semantic correspondences from object proposals
B. Ham, M. Cho, C. Schmid, and J. Ponce · 2017
Closest in time.
Anchornet: A weakly supervised network to learn geometry-sensitive features for semantic matching
D. Novotny, D. Larlus, and A. Vedaldi · 2017
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Unsupervised learning of object landmarks by factorized spatial embeddings
J. Thewlis, H. Bilen, and A. Vedaldi · 2017
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Fast multi-image matching via density-based clustering
R. Tron, X. Zhou, C. Esteves, and K. Daniilidis · 2017
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Deep semantic feature matching
N. Ufer and B. Ommer · 2017
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