Y. Amit and D. Geman, A Computational Model for Visual Selection, Neural Computation, vol.39, issue.3, 1999.
DOI : 10.1038/381520a0

M. Andreetto, L. Zelnik-manor, and P. Perona, Unsupervised learning of categorical segments in image collections, 2008.

T. L. Berg, A. C. Berg, and J. Shih, Automatic Attribute Discovery and Characterization from Noisy Web Data, ECCV, 2010.
DOI : 10.1007/978-3-642-15549-9_48

L. Bourdev and J. Malik, Poselets: Body part detectors trained using 3D human pose annotations, 2009 IEEE 12th International Conference on Computer Vision, 2009.
DOI : 10.1109/ICCV.2009.5459303

K. Chatfield, V. Lempitsky, A. Vedaldi, and A. Zisserman, The devil is in the details: an evaluation of recent feature encoding methods, Procedings of the British Machine Vision Conference 2011, 2011.
DOI : 10.5244/C.25.76

J. Deng, J. Krause, and L. Fei-fei, Fine-Grained Crowdsourcing for Fine-Grained Recognition, 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013.
DOI : 10.1109/CVPR.2013.81

J. Deng, S. Satheesh, A. Berg, and L. Fei-fei, Fast and balanced: Efficient label tree learning for large scale object recognition, NIPS, 2011.

J. Donahue and K. Grauman, Annotator rationales for visual recognition, 2011 International Conference on Computer Vision, p.5, 2011.
DOI : 10.1109/ICCV.2011.6126394

M. Douze, A. Ramisa, and C. Schmid, Combining attributes and Fisher vectors for efficient image retrieval, CVPR 2011, p.5, 2011.
DOI : 10.1109/CVPR.2011.5995595

URL : https://hal.archives-ouvertes.fr/inria-00566293

I. Endres, A. Farhadi, D. Hoiem, and D. A. Forsyth, The benefits and challenges of collecting richer object annotations, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Workshops, 2010.
DOI : 10.1109/CVPRW.2010.5543183

M. Everingham, A. Zisserman, C. Williams, and L. V. , The PASCAL visual obiect classes challenge 2007 (VOC2007) results, 2007.

A. Farhadi, I. Endres, and D. Hoiem, Attribute-centric recognition for cross-category generalization, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010.
DOI : 10.1109/CVPR.2010.5539924

A. Farhadi, I. Endres, D. Hoiem, and D. Forsyth, Describing objects by their attributes, 2009 IEEE Conference on Computer Vision and Pattern Recognition, 2005.
DOI : 10.1109/CVPR.2009.5206772

A. Farhadi, M. Hejrati, M. A. Sadeghi, P. Young, C. Rashtchian et al., Every Picture Tells a Story: Generating Sentences from Images, ECCV, 2005.
DOI : 10.1007/978-3-642-15561-1_2

L. Fei-fei, R. Fergus, and P. Perona, A Bayesian approach to unsupervised one-shot learning of object categories, ICCV, issue.3, 2003.

P. F. Felzenszwalb, R. B. Girshick, D. Mcallester, and D. Ramanan, Object Detection with Discriminatively Trained Part-Based Models, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.32, issue.9, pp.1627-1645, 2010.
DOI : 10.1109/TPAMI.2009.167

P. F. Felzenszwalb, R. B. Girshick, and D. A. Mcallester, Cascade object detection with deformable part models, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010.
DOI : 10.1109/CVPR.2010.5539906

R. B. Girshick, P. F. Felzenszwalb, and D. Mcallester, Discriminatively trained deformable part models, release 5, p.5

D. Hoiem, Y. Chodpathumwan, and Q. Dai, Diagnosing Error in Object Detectors, ECCV, 2012.
DOI : 10.1007/978-3-642-33712-3_25

I. Kokkinos, Shufflets: Shared Mid-level Parts for Fast Object Detection, 2013 IEEE International Conference on Computer Vision, p.7, 2013.
DOI : 10.1109/ICCV.2013.176

A. Kovashka, D. Parikh, and K. Grauman, Whittlesearch: Image search with relative attribute feedback, CVPR, p.5, 2012.

G. Kulkarni, V. Premraj, S. Dhar, S. Li, Y. Choi et al., Baby talk: Understanding and generating simple image descriptions, CVPR 2011, p.3, 2011.
DOI : 10.1109/CVPR.2011.5995466

N. Kumar, P. Belhumeur, and S. Nayar, FaceTracer: A Search Engine for Large Collections of Images with Faces, ECCV, 2008.
DOI : 10.1007/978-3-540-88693-8_25

N. Kumar, A. C. Berg, P. N. Belhumeur, and S. K. Nayar, Attribute and simile classifiers for face verification, 2009 IEEE 12th International Conference on Computer Vision, 2009.
DOI : 10.1109/ICCV.2009.5459250

C. Lampert, H. Nickisch, and S. Harmeling, Learning to detect unseen object classes by between-class attribute transfer, 2009 IEEE Conference on Computer Vision and Pattern Recognition, p.5, 2009.
DOI : 10.1109/CVPR.2009.5206594

C. H. Lampert, Detecting objects in large image collections and videos by efficient subimage retrieval, 2009 IEEE 12th International Conference on Computer Vision, 2009.
DOI : 10.1109/ICCV.2009.5459359

S. Maji, Discovering a Lexicon of Parts and Attributes, ECCV Workshop, 2012.
DOI : 10.1007/978-3-642-33885-4_3

S. Maji, J. Kannala, E. Rahtu, M. Blaschko, and A. Vedaldi, Finegrained visual classification of aircraft, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00842101

K. Matzen and N. Snavely, NYC3DCars: A Dataset of 3D Vehicles in Geographic Context, 2013 IEEE International Conference on Computer Vision, 2013.
DOI : 10.1109/ICCV.2013.99

M. Mitzenmacher and E. Upfal, Probability and computing -randomized algorithms and probabilistic analysis, CUP, issue.6, 2005.

V. Ordonez, G. Kulkarni, and T. L. Berg, Im2text: Describing images using 1 million captioned photographs, NIPS, 2011.

D. Parikh and G. Grauman, Interactively building a discriminative vocabulary of nameable attributes, CVPR 2011, p.5, 2011.
DOI : 10.1109/CVPR.2011.5995451

D. Parikh and K. Grauman, Relative attributes, 2011 International Conference on Computer Vision, 2011.
DOI : 10.1109/ICCV.2011.6126281

A. Parkash and D. Parikh, Attributes for Classifier Feedback, ECCV, 2012.
DOI : 10.1007/978-3-642-33712-3_26

O. Russakovsky and L. Fei-fei, Attribute learning in large-scale datasets. ECCV Workshop Parts and Attributes, p.5, 2010.

B. C. Russel, A. Torralba, K. P. Murphy, and W. T. Freeman, LabelMe: A Database and Web-Based Tool for Image Annotation, International Journal of Computer Vision, vol.3, issue.1, 2005.
DOI : 10.1007/s11263-007-0090-8

B. Siddiquie, R. S. Feris, and L. S. Davis, Image ranking and retrieval based on multi-attribute queries, CVPR 2011, 2011.
DOI : 10.1109/CVPR.2011.5995329

L. Torresani, M. Summer, and A. Fitzgibbon, Efficient Object Category Recognition Using Classemes, ECCV, p.5, 2010.
DOI : 10.1007/978-3-642-15549-9_56

C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie, The caltech-ucsd birds-200-2011 dataset, 2011.

G. Wang and D. Forsyth, Joint learning of visual attributes, object classes and visual saliency, 2009 IEEE 12th International Conference on Computer Vision, 2009.
DOI : 10.1109/ICCV.2009.5459194

G. Wang, D. Forsyth, and D. Hoiem, Comparative object similarity for improved recognition with few or no examples, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, p.5, 2010.
DOI : 10.1109/CVPR.2010.5539955

J. Wang, K. Markert, and M. Everingham, Learning Models for Object Recognition from Natural Language Descriptions, Procedings of the British Machine Vision Conference 2009, 2009.
DOI : 10.5244/C.23.2

Y. Wang and G. Mori, A Discriminative Latent Model of Object Classes and Attributes, ECCV, p.5, 2010.
DOI : 10.1007/978-3-642-15555-0_12

X. Zhu, C. Vondrick, D. Ramanan, and C. Fowlkes, Do We Need More Training Data or Better Models for Object Detection?, Procedings of the British Machine Vision Conference 2012, p.5, 2012.
DOI : 10.5244/C.26.80

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.259.7748