S. Belongie, J. Malik, and J. Puzicha, Shape matching and object recognition using shape contexts. TPAMI, 2002.

A. C. Berg, T. L. Berg, and J. Malik, Shape Matching and Object Recognition Using Low Distortion Correspondences, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005.
DOI : 10.1109/CVPR.2005.320
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.72.8044

W. Brendel and S. Todorovic, Learning spatiotemporal graphs of human activities, 2011 International Conference on Computer Vision, pp.778-785, 2011.
DOI : 10.1109/ICCV.2011.6126316

T. S. Caetano, J. J. Mcauley, L. Cheng, Q. V. Le, and A. J. Smola, Learning graph matching, 2009.
DOI : 10.1109/tpami.2009.28
URL : http://arxiv.org/abs/0806.2890

M. Cho, J. Lee, and K. M. Lee, Reweighted Random Walks for Graph Matching, ECCV, 2010.
DOI : 10.1007/978-3-642-15555-0_36

M. Cho and K. M. Lee, Progressive graph matching: Making a move of graphs via probabilistic voting, CVPR, 2012.

D. Conte, P. Foggia, C. Sansone, and M. Vento, Thirty years of graph matching in pattern recognition. IJPRAI, 2004.
URL : https://hal.archives-ouvertes.fr/hal-01408706

T. Cour, P. Srinivasan, and J. Shi, Balanced graph matching, NIPS, 2007.

N. Dalal and B. Triggs, Histograms of Oriented Gradients for Human Detection, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005.
DOI : 10.1109/CVPR.2005.177
URL : https://hal.archives-ouvertes.fr/inria-00548512

J. Davis and P. Domingos, Bottom-up learning of Markov network structure, ICML, 2010.

O. Duchenne, F. Bach, I. Kweon, and J. Ponce, A tensor-based algorithm for high-order graph matching, CVPR, 2009.
URL : https://hal.archives-ouvertes.fr/hal-01063322

O. Duchenne, A. Joulin, and J. Ponce, A graph-matching kernel for object categorization, 2011 International Conference on Computer Vision, 2011.
DOI : 10.1109/ICCV.2011.6126445
URL : https://hal.archives-ouvertes.fr/hal-00650345

S. Gold and A. Rangarajan, A graduated assignment algorithm for graph matching, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.18, issue.4, 1996.
DOI : 10.1109/34.491619

S. Hare, A. Saffari, and P. H. Torr, Efficient online structured output learning for keypoint-based object tracking, 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012.
DOI : 10.1109/CVPR.2012.6247889

T. Joachims, T. Finley, and C. Yu, Cutting-plane training of structural SVMs, Machine Learning, 2009.
DOI : 10.1007/s10994-009-5108-8

S. Lee, V. Ganapahthi, and D. Koller, Efficient Structure Learning of Markov Networks using L1-Regularization, NIPS, 2006.

M. Leordeanu and M. Hebert, A spectral technique for correspondence problems using pairwise constraints, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, 2005.
DOI : 10.1109/ICCV.2005.20

M. Leordeanu, M. Hebert, and R. Sukthankar, Beyond Local Appearance: Category Recognition from Pairwise Interactions of Simple Features, 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007.
DOI : 10.1109/CVPR.2007.383091

M. Leordeanu, M. Hebert, and R. Sukthankar, An integer projected fixed point method for graph matching and map inference, NIPS, 2009. [21] M. Leordeanu, R. Sukthankar, and M. Hebert. Unsupervised learning for graph matching. IJCV, 2012.

D. G. Lowe, Distinctive image features from scale-invariant keypoints . IJCV, 2004.

J. Matas, O. Chum, M. Urban, and T. Pajdla, Robust wide baseline stereo from maximally stable extremal regions, BMVC, 2002.

K. Mikolajczyk and C. Schmid, Scale and affine invariant interest point detectors. IJCV, 2004.
DOI : 10.1023/b:visi.0000027790.02288.f2

S. Nowozin, P. Gehler, and C. Lampert, On Parameter Learning in CRF-Based Approaches to Object Class Image Segmentation, 2010.
DOI : 10.1007/978-3-642-15567-3_8

D. Pachauri, M. Collins, V. Singh, R. Kondor, V. S. Deepti-pachauri et al., Incorporating domain knowledge in matching problems via harmonic analysis, ICML, 2012.

A. Sharma, R. Horaud, J. Cech, and E. Boyer, Topologically-robust 3D shape matching based on diffusion geometry and seed growing, CVPR 2011, 2011.
DOI : 10.1109/CVPR.2011.5995455
URL : https://hal.archives-ouvertes.fr/inria-00590280

M. Szummer, P. Kohli, and D. Hoiem, Learning CRFs Using Graph Cuts, ECCV, 2008.
DOI : 10.1007/978-3-540-88688-4_43
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.141.7402

B. Taskar, C. Guestrin, and D. Koller, Max-margin markov networks, NIPS, 2003.

L. Torresani, V. Kolmogorov, and C. Rother, Feature Correspondence Via Graph Matching: Models and Global Optimization, ECCV, 2008.
DOI : 10.1007/978-3-540-88688-4_44
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.146.4872

I. Tsochantaridis, T. Joachims, T. Hofmann, and Y. Altun, Large margin methods for structured and interdependent output variables, JMLR, 2005.

S. Umeyama, An eigen decomposition approach to weighted graph matching problems, Trans. PAMI, 1988.
DOI : 10.1109/34.6778

B. Yao and L. Fei-fei, Action Recognition with Exemplar Based 2.5D Graph Matching, ECCV, 2012.
DOI : 10.1007/978-3-642-33765-9_13