R. Arandjelovi? and A. Zisserman, Visual vocabulary with a semantic twist, ACCV, 2014.

Y. Avrithis and Y. Kalantidis, Approximate gaussian mixtures for large scale vocabularies, ECCV, vol.4, p.5, 2012.

H. Azizpour, A. S. Razavian, J. Sullivan, A. Maki, and S. Carlsson, From generic to specific deep representations for visual recognition, vol.2, p.5, 2014.

A. Babenko and V. Lempitsky, Aggregating deep convolutional features for image retrieval, ICCV, vol.2, p.5, 2015.

A. Babenko, A. Slesarev, A. Chigorin, and V. Lempitsky, Neural codes for image retrieval, ECCV, 2014.

S. Bagon, O. Brostovski, M. Galun, and M. Irani, Detecting and sketching the common, CVPR, p.3, 2010.

M. Cho, S. Kwak, C. Schmid, and J. Ponce, Unsupervised object discovery and localization in the wild: Part-based matching with bottom-up region proposals, CVPR, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01110036

O. Chum and J. Matas, Unsupervised discovery of co-occurrence in sparse high dimensional data, CVPR, 2002.

W. Dong, M. Charikar, and K. Li, Efficient k-nearest neighbor graph construction for generic similarity measures, WWW, 2011.

S. Gammeter, L. Bossard, T. Quack, and L. V. Gool, I know what you did last summer: Object-level auto-annotation of holiday snaps, ICCV, 2009.

A. Gordo, J. Almazan, J. Revaud, and D. Larlus, Deep image retrieval: Learning global representations for image search, ECCV, vol.2, p.5, 2016.

A. Gordo, J. Almazan, J. Revaud, and D. Larlus, End-to-end learning of deep visual representations for image retrieval, vol.2, p.7, 2016.

C. H. Hubbell, An input-output approach to clique identification, Sociometry, issue.6, 1965.

A. Iscen, Y. Avrithis, G. Tolias, T. Furon, and O. Chum, Fast spectral ranking for similarity search, CVPR, vol.2, p.6, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01839744

A. Iscen, G. Tolias, Y. Avrithis, T. Furon, and O. Chum, Efficient diffusion on region manifolds: Recovering small objects with compact cnn representations, CVPR, p.10, 2009.
URL : https://hal.archives-ouvertes.fr/hal-01505470

H. Jégou, M. Douze, and C. Schmid, Improving bag-of-features for large scale image search, IJCV, vol.87, issue.3, pp.316-336, 2002.

D. Jeong, S. Choo, W. Seo, and N. I. Cho, Regional deep feature aggregation for image retrieval, ICASSP, 2017.

A. Jimenez, J. M. Alvarez, and X. Giro-i-nieto, Class-weighted convolutional features for visual instance search, vol.3, p.10, 2017.

Y. Kalantidis, C. Mellina, and S. Osindero, Cross-dimensional weighting for aggregated deep convolutional features, arXiv, vol.5, p.7, 2004.

L. Katz, A new status index derived from sociometric analysis, Psychometrika, vol.18, issue.1, pp.39-43, 1953.

G. Kim and A. Torralba, Unsupervised detection of regions of interest using iterative link analysis, NIPS, 2009.

J. Kim and S. Yoon, Regional attention based deep feature for image retrieval, BMVC, issue.3, 2018.

J. Knopp, J. Sivic, and T. Pajdla, Avoiding confusing features in place recognition, ECCV, 2010.

S. Kwak, M. Cho, I. Laptev, J. Ponce, and C. Schmid, Unsupervised object discovery and tracking in video collections, CVPR, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01153017

Z. Laskar and J. Kannala, Context aware query image representation for particular object retrieval, Scandinavian Conference on Image Analysis, 2017.

N. Mej, Networks: an introduction, 2010.

K. Mikolajczyk and J. Matas, Improving descriptors for fast tree matching by optimal linear projection, CVPR, 2007.

E. Mohedano, K. Mcguinness, X. Giro-i-nieto, and N. E. O'connor, Saliency weighted convolutional features for instance search, vol.3, p.10, 2017.

J. Nocedal and S. Wright, Numerical optimization, 2006.

H. Noh, A. Araujo, J. Sim, T. Weyand, and B. Han, Large-scale image retrieval with attentive deep local features, vol.2, p.10, 2016.

A. Oliva and A. Torralba, Building the gist of a scene: The role of global image features in recognition, Progress in brain research, vol.155, issue.1, pp.23-36, 2006.

D. Omercevic, R. Perko, A. T. Targhi, J. Eklundh, and A. Leonardis, Vegetation segmentation for boosting performance of mser feature detector, Computer Vision Winter Workshop, 2008.

L. Page, S. Brin, R. Motwani, and T. Winograd, The PageRank citation ranking: bringing order to the web, vol.3, p.6, 1999.

S. Pang, J. Ma, J. Xue, J. Zhu, and V. Ordonez, Image retrieval using heat diffusion for deep feature aggregation, 2018.

J. Philbin, O. Chum, M. Isard, J. Sivic, and A. Zisserman, Object retrieval with large vocabularies and fast spatial matching, CVPR, 2007.

J. Philbin, O. Chum, M. Isard, J. Sivic, and A. Zisserman, Lost in quantization: Improving particular object retrieval in large scale image databases, CVPR, 2008.

F. Radenovi?, A. Iscen, G. Tolias, Y. Avrithis, and O. Chum, Revisiting oxford and paris: Large-scale image retrieval benchmarking, CVPR, vol.2, 2018.

F. Radenovi?, G. Tolias, and O. Chum, CNN image retrieval learns from bow: Unsupervised fine-tuning with hard examples, ECCV, 2005.

F. Radenovi?, G. Tolias, and O. Chum, Fine-tuning cnn image retrieval with no human annotation, IEEE Trans. PAMI, p.10, 2009.

A. S. Razavian, J. Sullivan, S. Carlsson, and A. Maki, Visual instance retrieval with deep convolutional networks. ITE Transactions on Media Technology and Applications, vol.4, p.10, 2003.

M. Rubinstein, A. Joulin, J. Kopf, and C. Liu, Unsupervised joint object discovery and segmentation in internet images, CVPR, 2013.
URL : https://hal.archives-ouvertes.fr/hal-01064227

A. Salvador, X. Giró-i-nieto, F. Marqués, and S. Satoh, Faster r-cnn features for instance search, CVPRW, vol.2, p.10, 2016.

R. R. Selvaraju, A. Das, R. Vedantam, M. Cogswell, D. Parikh et al., Grad-CAM: Why did you say that? visual explanations from deep networks via gradient-based localization, 2016.

M. Shi, Y. Avrithis, and H. Jegou, Early burst detection for memoryefficient image retrieval, CVPR, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01146533

O. Simeoni, A. Iscen, G. Tolias, Y. Avrithis, and O. Chum, Unsupervised object discovery for instance recognition, WACV, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01842143

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

J. Sivic and A. Zisserman, Video Google: A text retrieval approach to object matching in videos, ICCV, vol.1, 2003.

J. Song, T. He, L. Gao, X. Xu, and H. T. Shen, Deep region hashing for efficient large-scale instance search from images, vol.3, p.10

G. Tolias, Y. Avrithis, and H. Jégou, Image search with selective match kernels: aggregation across single and multiple images, IJCV, issue.2, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01131898

G. Tolias, Y. Kalantidis, and Y. Avrithis, Symcity: Feature selection by symmetry for large scale image retrieval, ACM Multimedia, 2012.

G. Tolias, R. Sicre, and H. Jégou, Particular object retrieval with integral max-pooling of cnn activations, ICLR, p.10, 2008.
URL : https://hal.archives-ouvertes.fr/hal-01842218

P. Turcot and D. G. Lowe, Better matching with fewer features: The selection of useful features in large database recognition problems, ICCVW, vol.2, p.3, 2009.

S. Vigna, Spectral ranking, 2009.

S. Wang and S. Jiang, Instre: a new benchmark for instance-level object retrieval and recognition, ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), vol.11, p.37, 2015.

L. Zheng, S. Wang, J. Wang, and Q. Tian, Accurate image search with multi-scale contextual evidences, IJCV, vol.120, issue.1, pp.1-13, 2016.

B. Zhou, A. Khosla, A. Lapedriza, A. Oliva, and A. Torralba, Learning deep features for discriminative localization, cvpr, 2004.

D. Zhou, J. Weston, A. Gretton, O. Bousquet, and B. Schölkopf, Ranking on data manifolds, NIPS, 2003.

Y. Zhu, J. Wang, L. Xie, and L. Zheng, Attention-based pyramid aggregation network for visual place recognition, 2018.