R. Arandjelovic and A. Zisserman, Three things everyone should know to improve object retrieval, CVPR, pp.2911-2918, 2012.

D. Barath and L. Hajder, Novel ways to estimate homography from local affine transformations, 2016.

A. Baumberg, Reliable feature matching across widely separated views, CVPR, vol.1, pp.774-781, 2000.

J. Blom, Topological and Geometrical Aspects of Image Structure, 1992.

F. Cao, J. Lisani, J. Morel, P. Musé, and F. Sur, A Theory of Shape Identification, 2008.
URL : https://hal.archives-ouvertes.fr/inria-00319719

D. Detone, T. Malisiewicz, and A. Rabinovich, Deep image homography estimation, 2016.

E. Farhan and R. Hagege, Geometric expansion for local feature analysis and matching, SIAM Journal on Imaging Sciences, vol.8, issue.4, pp.2771-2813, 2015.

E. Farhan, E. Meir, and R. Hagege, Local Region Expansion: a Method for Analyzing and Refining Image Matches, Image Processing On Line, vol.7, pp.386-398, 2017.

M. A. Fischler and R. C. Bolles, Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography, Communications of the ACM, vol.24, issue.6, pp.381-395, 1981.

R. Hartley and A. Zisserman, Multiple view geometry in computer vision, 2003.

D. C. Hauagge and N. Snavely, Image matching using local symmetry features, 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp.206-213, 2012.

T. Iijima, Basic equation of figure and and observational transformation, Computers, Controls, vol.2, issue.4, pp.70-77, 1971.

T. Lin, M. Maire, S. Belongie, J. Hays, P. Perona et al., Microsoft coco: Common objects in context, ECCV, pp.740-755, 2014.

T. Lindeberg, Scale-Space Theory in Computer Vision. Royal Institute of Technology, 1993.

T. Lindeberg and J. Garding, Shape-adapted smoothing in estimation of 3-D depth cues from affine distortions of local 2-D brightness structure, ECCV, pp.389-400, 1994.

D. Lowe, Distinctive image features from scale-invariant keypoints, IJCV, vol.60, issue.2, pp.91-110, 2004.

J. Matas, O. Chum, M. Urban, and T. Pajdla, Robust wide-baseline stereo from maximally stable extremal regions, IVC, vol.22, issue.10, pp.761-767, 2004.

K. Mikolajczyk and C. Schmid, An affine invariant interest point detector. ECCV, vol.1, pp.128-142, 2002.

K. Mikolajczyk and C. Schmid, Scale and Affine Invariant Interest Point Detectors. IJCV, vol.60, issue.1, pp.63-86, 2004.

K. Mikolajczyk, T. Tuytelaars, C. Schmid, A. Zisserman, J. Matas et al., A comparison of affine region detectors, International journal of computer vision, vol.65, issue.1-2, pp.43-72, 2005.
URL : https://hal.archives-ouvertes.fr/inria-00548528

A. Mishchuk, D. Mishkin, F. Radenovic, and J. Matas, Working hard to know your neighbor's margins: Local descriptor learning loss, Advances in Neural Information Processing Systems, pp.4826-4837, 2017.

D. Mishkin, J. Matas, and M. Perdoch, MODS: Fast and robust method for two-view matching, vol.141, pp.81-93, 2015.

D. Mishkin, F. Radenovic, and J. Matas, Repeatability is not enough: Learning affine regions via discriminability, Proceedings of the European Conference on Computer Vision (ECCV), pp.284-300, 2018.

L. Moisan, P. Moulon, and P. Monasse, Automatic Homographic Registration of a Pair of Images, with A Contrario Elimination of, Outliers. IPOL, vol.2, pp.56-73, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00711852

L. Moisan, P. Moulon, and P. Monasse, Fundamental Matrix of a Stereo Pair, with A Contrario Elimination of Outliers, IPOL, vol.6, pp.89-113, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01386806

J. Morel and G. Yu, ASIFT: A new framework for fully affine invariant image comparison, SIAM Journal on Imaging Sciences, vol.2, issue.2, pp.438-469, 2009.

P. Musé, F. Sur, F. Cao, and Y. Gousseau, Unsupervised thresholds for shape matching, ICIP, 2003.

P. Musé, F. Sur, F. Cao, Y. Gousseau, and J. Morel, An A Contrario Decision Method for Shape Element Recognition, IJCV, vol.69, issue.3, pp.295-315, 2006.

Y. Pang, W. Li, Y. Yuan, and J. Pan, Fully affine invariant SURF for image matching, Neurocomputing, vol.85, pp.6-10, 2012.

R. Raguram, O. Chum, M. Pollefeys, J. Matas, and J. Frahm, USAC: a universal framework for random sample consensus, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.35, issue.8, pp.2022-2038, 2013.

M. Rais, G. Facciolo, E. Meinhardt-llopis, M. J. , .. et al., Accurate motion estimation through random sample aggregated consensus, 2017.

C. Raposo and J. P. Barreto, Theory and practice of structure-from-motion using affine correspondences, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.5470-5478, 2016.

I. Rey-otero, M. Delbracio, and J. Morel, Comparing feature detectors: A bias in the repeatability criteria, 2015 IEEE International Conference on Image Processing (ICIP), pp.3024-3028, 2015.

I. Rocco, R. Arandjelovic, and J. Sivic, Convolutional neural network architecture for geometric matching, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01859616

M. Rodriguez and R. Grompone-von-gioi, Affine invariant image comparison under repetitive structures, ICIP, pp.1203-1207, 2018.

M. Rodriguez, J. Delon, and M. J. , Covering the space of tilts. application to affine invariant image comparison, SIIMS, vol.11, issue.2, pp.1230-1267, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01589522

M. Rodriguez, J. Delon, and J. Morel, Fast affine invariant image matching, IPOL, vol.8, pp.251-281, 2018.
URL : https://hal.archives-ouvertes.fr/hal-02002845

M. Rodriguez, G. Facciolo, R. Grompone-von-gioi, P. Musé, J. Morel et al., Siftaid: boosting sift with an affine invariant descriptor based on convolutional neural networks, ICIP, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02016010

K. Simonyan and A. Zisserman, Very deep convolutional networks for large-scale image recognition, 2014.

T. Tuytelaars and L. Van-gool, Wide baseline stereo matching based on local, affinely invariant regions, BMVC, pp.412-425, 2000.

T. Tuytelaars and L. Van-gool, Matching Widely Separated Views Based on Affine Invariant Regions, IJCV, vol.59, issue.1, pp.61-85, 2004.

T. Tuytelaars, L. Van-gool, and O. , Content-based image retrieval based on local affinely invariant regions. Int. Conf. on Visual Information Systems, pp.493-500, 1999.

Y. Zheng and D. Doermann, Robust point matching for nonrigid shapes by preserving local neighborhood structures, IEEE transactions on pattern analysis and machine intelligence, vol.28, pp.643-649, 2006.

C. L. Zitnick and K. Ramnath, Edge foci interest points, 2011 International Conference on Computer Vision, pp.359-366, 2011.