R. Arandjelovi´carandjelovi´c and A. Zisserman, Multiple queries for large scale specific object retrieval, Proc. BMVC, 2012.

R. Arandjelovi´carandjelovi´c and A. Zisserman, All about VLAD, Proc. CVPR, 2013.

K. Chatfield, R. Arandjelovi´carandjelovi´c, O. M. Parkhi, and A. Zisserman, On-the-fly learning for visual search of large-scale image and video datasets, International Journal of Multimedia Information Retrieval, vol.38, issue.2, 2015.
DOI : 10.1007/s13735-015-0077-0

D. Chen, X. Cao, F. Wen, and J. Sun, Blessing of Dimensionality: High-Dimensional Feature and Its Efficient Compression for Face Verification, 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013.
DOI : 10.1109/CVPR.2013.389

K. Crammer and Y. Singer, On the algorithmic implementation of multiclass kernelbased vector machines, JMLR, vol.2, pp.265-292, 2001.

K. He, X. Zhang, S. Ren, and J. Sun, Deep Residual Learning for Image Recognition, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
DOI : 10.1109/CVPR.2016.90

G. B. Huang, M. Ramesh, T. Berg, and E. Learned-miller, Labeled faces in the wild: A database for studying face recognition in unconstrained environments, 2007.

H. Jégou, M. Douze, C. Schmid, and P. Pérez, Aggregating local descriptors into a compact image representation, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010.
DOI : 10.1109/CVPR.2010.5540039

H. Jégou, F. Perronnin, M. Douze, J. Sánchez, P. Pérez et al., Aggregating Local Image Descriptors into Compact Codes, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.34, issue.9, 2012.
DOI : 10.1109/TPAMI.2011.235

A. Krizhevsky, I. Sutskever, and G. E. Hinton, ImageNet classification with deep convolutional neural networks, NIPS, pp.1106-1114, 2012.

M. Mathias, R. Benenson, M. Pedersoli, and L. Van-gool, Face Detection without Bells and Whistles, ECCV, 2014.
DOI : 10.1007/978-3-319-10593-2_47

O. M. Parkhi, A. Vedaldi, and A. Zisserman, Deep Face Recognition, Procedings of the British Machine Vision Conference 2015, 2015.
DOI : 10.5244/C.29.41

O. Paul, G. Awad, M. Michel, J. Fiscus, W. Kraaij et al., TRECVID 2011 ? an overview of the goals, tasks, data, evaluation mechanisms and metrics, TRECVID, 2011.

P. Pérez, M. Gangnet, and A. Blake, Poisson image editing, ACM Transactions on Graphics, vol.22, issue.3, pp.313-318, 2003.
DOI : 10.1145/882262.882269

F. Perronnin, Z. Akata, Z. Harchaoui, and C. Schmid, Towards good practice in largescale learning for image classification, Proc. CVPR, pp.3482-3489, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00690014

J. C. Platt, Fast training of support vector machines using sequential minimal optimization, Advances in Kernel Methods -Support Vector Learning, pp.185-208, 1999.

F. Schroff, D. Kalenichenko, and J. Philbin, FaceNet: A unified embedding for face recognition and clustering, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
DOI : 10.1109/CVPR.2015.7298682

J. A. Shaw and E. A. Fox, Combination of multiple searches, The Second Text REtrieval Conference (TREC-2), pp.243-252, 1994.

K. Simonyan and A. Zisserman, Very deep convolutional networks for large-scale image recognition, International Conference on Learning Representations, 2015.

A. Vedaldi and K. Lenc, Matconvnet ? convolutional neural networks for matlab, Proc. ACMM, 2015.

L. Wolf, I. Hassner, and . Maoz, Face recognition in unconstrained videos with matched backgroundsimilarity, Proc. CVPR, 2011.

Z. Wu, Q. Ke, J. Sun, and H. Shum, Scalable face image retrieval with identity-based quantization and multireference reranking, IEEE PAMI, vol.33, issue.10, pp.1991-2001, 2011.

X. Xiong and F. De-la-torre, Supervised Descent Method and Its Applications to Face Alignment, 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013.
DOI : 10.1109/CVPR.2013.75

B. Zhou, A. Lapedriza, J. Xiao, A. Torralba, and A. Oliva, Learning deep features for scene recognition using places database, NIPS, pp.487-495, 2014.