P. Agrawal, R. Girshick, and J. Malik, Analyzing the Performance of Multilayer Neural Networks for Object Recognition, Computer Vision?ECCV 2014, pp.329-344, 2014.
DOI : 10.1007/978-3-319-10584-0_22
URL : http://arxiv.org/pdf/1407.1610

R. Arandjelovi´carandjelovi´c and A. Zisserman, Smooth object retrieval using a bag of boundaries, ICCV, 2011.

M. Aubry, D. Maturana, A. A. Efros, B. C. Russell, and J. Sivic, Seeing 3D Chairs: Exemplar Part-Based 2D-3D Alignment Using a Large Dataset of CAD Models, 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2008.
DOI : 10.1109/CVPR.2014.487
URL : https://hal.archives-ouvertes.fr/hal-01057240

M. Aubry and B. C. Russell, Understanding Deep Features with Computer-Generated Imagery, 2015 IEEE International Conference on Computer Vision (ICCV), 2004.
DOI : 10.1109/ICCV.2015.329
URL : https://hal.archives-ouvertes.fr/hal-01240849

G. Baatz, O. Saurer, K. Köser, and M. Pollefeys, Large Scale Visual Geo-Localization of Images in Mountainous Terrain, ECCV, 2012.
DOI : 10.1007/978-3-642-33709-3_37

S. Bell and K. Bala, Learning visual similarity for product design with convolutional neural networks, ACM Transactions on Graphics, vol.34, issue.4, p.2015
DOI : 10.1145/1390156.1390303

Y. Bengio, Deep learning of representations for unsupervised and transfer learning, JMLR Workshop on Unsupervised and Transfer Learning, 2012.

T. Chen, Z. Zhu, A. Shamir, S. Hu, and D. Cohen-or, 3-Sweep, ACM Transactions on Graphics, vol.32, issue.6, p.32195, 2013.
DOI : 10.1145/2508363.2508378

C. B. Choy, M. Stark, S. Corbett-davies, and S. Savarese, Enriching object detection with 2D-3D registration and continuous viewpoint estimation, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
DOI : 10.1109/CVPR.2015.7298866

O. Chum, J. Philbin, J. Sivic, M. Isard, and A. Zisserman, Total Recall: Automatic Query Expansion with a Generative Feature Model for Object Retrieval, 2007 IEEE 11th International Conference on Computer Vision, 2007.
DOI : 10.1109/ICCV.2007.4408891

R. Collobert, K. Kavukcuoglu, and C. Farabet, Torch7: A matlab-like environment for machine learning, BigLearn, NIPS Workshop, number EPFL-CONF-192376, 2011.

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

A. Dosovitskiy and T. Brox, Inverting Visual Representations with Convolutional Networks, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
DOI : 10.1109/CVPR.2016.522
URL : http://arxiv.org/pdf/1506.02753

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

S. Fidler, S. Dickinson, and R. Urtasun, 3D object detection and viewpoint estimation with a deformable 3D cuboid model, NIPS, 2012.

Y. Ganin and V. Lempitsky, Unsupervised domain adaptation by backpropagation, Proceedings of The 32nd International Conference on Machine Learning, pp.1180-1189, 2015.

R. Girshick, Fast R-CNN, 2015 IEEE International Conference on Computer Vision (ICCV), 2015.
DOI : 10.1109/ICCV.2015.169

R. Girshick, J. Donahue, T. Darrell, and J. Malik, Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation, 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2008.
DOI : 10.1109/CVPR.2014.81
URL : http://arxiv.org/pdf/1311.2524

R. Guo and D. Hoiem, Beyond the Line of Sight: Labeling the Underlying Surfaces, Computer Vision?ECCV 2012, pp.761-774, 2012.
DOI : 10.1007/978-3-642-33715-4_55
URL : http://www.cs.cmu.edu/%7Edhoiem/publications/eccv2012_lineofsight_ruiqi.pdf

A. Gupta, A. A. Efros, and M. Hebert, Blocks World Revisited: Image Understanding Using Qualitative Geometry and Mechanics, ECCV, 2010.
DOI : 10.1007/978-3-642-15561-1_35
URL : http://www.cs.cmu.edu/%7Eabhinavg/blocksworld/blocksworld.pdf

S. Gupta, P. A. Arbeláez, R. B. Girshick, and J. Malik, Aligning 3D models to RGB-D images of cluttered scenes, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
DOI : 10.1109/CVPR.2015.7299105

S. Gupta, J. Hoffman, and J. Malik, Cross Modal Distillation for Supervision Transfer, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
DOI : 10.1109/CVPR.2016.309
URL : http://arxiv.org/pdf/1507.00448

K. He, X. Zhang, S. Ren, and J. Sun, Spatial pyramid pooling in deep convolutional networks for visual recognition, Computer Vision?ECCV 2014, pp.346-361, 2014.
DOI : 10.1109/tpami.2015.2389824
URL : http://arxiv.org/pdf/1406.4729

M. Hejrati and D. Ramanan, Analyzing 3D objects in cluttered images, NIPS, 2012

G. Hinton, O. Vinyals, and J. Dean, Distilling the knowledge in a neural network, NIPS Deep Learning Workshop, issue.3, 2014.

J. Hoffman, S. Guadarrama, E. Tzeng, R. Hu, J. Donahue et al., LSDA: Large scale detection through adaptation, NIPS, 2014.

Q. Huang, H. Wang, and V. Koltun, Single-view reconstruction via joint analysis of image and shape collections, Proceeding of SIGGRAPH), p.2015
DOI : 10.1145/15922.15903
URL : http://vladlen.info/papers/single-view-reconstruction.pdf

M. Irani and P. Anandan, Robust multi-sensor image alignment, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271), 1998.
DOI : 10.1109/ICCV.1998.710832

Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long et al., Caffe, Proceedings of the ACM International Conference on Multimedia, MM '14, pp.675-678, 2005.
DOI : 10.1145/2647868.2654889

N. Kholgade, T. Simon, A. Efros, and Y. Sheikh, 3D object manipulation in a single photograph using stock 3D models, ACM Transactions on Graphics, vol.33, issue.4, p.127, 2014.
DOI : 10.1111/j.1467-9868.2005.00503.x

A. Krizhevsky, I. Sutskever, and G. E. Hinton, ImageNet classification with deep convolutional neural networks, Communications of the ACM, vol.60, issue.6, 2002.
DOI : 10.1162/neco.2009.10-08-881
URL : http://dl.acm.org/ft_gateway.cfm?id=3065386&type=pdf

Y. Lecun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard et al., Backpropagation Applied to Handwritten Zip Code Recognition, Neural Computation, vol.1, issue.4, pp.541-551, 1989.
DOI : 10.1007/BF00133697

K. Lenc and A. Vedaldi, Understanding image representations by measuring their equivariance and equivalence, CVPR, 2015.
DOI : 10.1007/s11263-018-1098-y
URL : https://link.springer.com/content/pdf/10.1007%2Fs11263-018-1098-y.pdf

Y. Li, N. Snavely, D. Huttenlocher, and P. Fua, Worldwide pose estimation using 3D point clouds, ECCV, 2012.
DOI : 10.1007/978-3-642-33718-5_2
URL : https://infoscience.epfl.ch/record/201014/files/global_pose.pdf

Y. Li, H. Su, C. R. Qi, N. Fish, D. Cohen-or et al., Joint embeddings of shapes and images via CNN image purification, ACM Transactions on Graphics, vol.34, issue.6, p.2015
DOI : 10.1109/CVPR.2010.5540018

J. J. Lim, H. Pirsiavash, and A. Torralba, Parsing IKEA Objects: Fine Pose Estimation, 2013 IEEE International Conference on Computer Vision, 2006.
DOI : 10.1109/ICCV.2013.372
URL : http://people.csail.mit.edu/lim/paper/lpt_iccv2013.pdf

D. Lowe, Distinctive Image Features from Scale-Invariant Keypoints, International Journal of Computer Vision, vol.60, issue.2, pp.91-110, 2004.
DOI : 10.1023/B:VISI.0000029664.99615.94
URL : http://www.cs.ubc.ca/~lowe/papers/ijcv03.ps

T. Malisiewicz, A. Gupta, and A. A. Efros, Ensemble of exemplar-SVMs for object detection and beyond, 2011 International Conference on Computer Vision, 2011.
DOI : 10.1109/ICCV.2011.6126229
URL : http://www.cs.cmu.edu/%7Etmalisie/projects/iccv11/exemplarsvm-iccv11.pdf

J. L. Mundy, Object Recognition in the Geometric Era: A Retrospective, Toward Category-Level Object Recognition, pp.3-29, 2006.
DOI : 10.1007/11957959_1
URL : http://www.di.ens.fr/~ponce/mundy.pdf

X. Peng, K. Saenko, B. Sun, and K. Ali, Learning Deep Object Detectors from 3D Models, 2015 IEEE International Conference on Computer Vision (ICCV), 2007.
DOI : 10.1109/ICCV.2015.151
URL : http://arxiv.org/pdf/1412.7122

B. Pepik, R. Benenson, T. Ritschel, and B. Schiele, What is holding back convnets for detection? In Pattern Recognition, pp.517-528, 2007.
DOI : 10.1007/978-3-319-24947-6_43
URL : http://arxiv.org/pdf/1508.02844

B. Pepik, M. Stark, P. Gehler, and B. Schiele, Teaching 3D geometry to deformable part models, 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012.
DOI : 10.1109/CVPR.2012.6248075
URL : http://ps.is.tue.mpg.de/publications/59/get_file/

L. Roberts, Machine perception of 3-D solids, 1965.

A. Romero, N. Ballas, S. E. Kahou, A. Chassang, C. Gatta et al., Fitnets: Hints for thin deep nets. arXiv preprint arXiv:1412, 2014.

F. Rothganger, S. Lazebnik, C. Schmid, and J. Ponce, 3D Object Modeling and Recognition Using Local Affine-Invariant Image Descriptors and Multi-View Spatial Constraints, International Journal of Computer Vision, vol.17, issue.5, pp.231-259, 2006.
DOI : 10.1007/s11263-005-3674-1
URL : https://hal.archives-ouvertes.fr/inria-00548618

K. Simonyan and A. Zisserman, Very deep convolutional networks for large-scale image recognition. CoRR, abs, 1409.

S. Song and J. Xiao, Sliding Shapes for 3D Object Detection in Depth Images, ECCV, 2014.
DOI : 10.1007/978-3-319-10599-4_41
URL : http://vision.princeton.edu/projects/2014/SlidingShapes/paper.pdf

H. Su, Q. Huang, N. Mitra, Y. Li, and L. Guibas, Estimating image depth using shape collections, ACM Transactions on Graphics, vol.33, issue.4, p.2014
DOI : 10.1109/TPAMI.2013.87
URL : http://vecg.cs.ucl.ac.uk/Projects/SmartGeometry/image_shape_net/paper_docs/imageShapeNet_small_sigg14.pdf

H. Su, C. Qi, Y. Li, and L. Guibas, Render for CNN: Viewpoint Estimation in Images Using CNNs Trained with Rendered 3D Model Views, 2015 IEEE International Conference on Computer Vision (ICCV)
DOI : 10.1109/ICCV.2015.308
URL : http://arxiv.org/pdf/1505.05641

H. Su, F. Wang, E. Yi, and L. J. Guibas, 3D-Assisted Feature Synthesis for Novel Views of an Object, 2015 IEEE International Conference on Computer Vision (ICCV), pp.2677-2685, 2015.
DOI : 10.1109/ICCV.2015.307

B. Sun and K. Saenko, From Virtual to Reality: Fast Adaptation of Virtual Object Detectors to Real Domains, Proceedings of the British Machine Vision Conference 2014, p.3, 2014.
DOI : 10.5244/C.28.82
URL : http://www.bmva.org/bmvc/2014/files/abstract062.pdf

C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed et al., Going deeper with convolutions, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.1-9, 2015.
DOI : 10.1109/CVPR.2015.7298594
URL : http://arxiv.org/pdf/1409.4842

A. Torralba and A. A. Efros, Unbiased look at dataset bias, CVPR 2011, 2011.
DOI : 10.1109/CVPR.2011.5995347
URL : http://people.csail.mit.edu/torralba/publications/datasets_cvpr11.pdf

E. Tzeng, J. Hoffman, T. Darrell, and K. Saenko, Simultaneous Deep Transfer Across Domains and Tasks, 2015 IEEE International Conference on Computer Vision (ICCV), 2015.
DOI : 10.1109/ICCV.2015.463
URL : http://arxiv.org/pdf/1510.02192

J. Uijlings, K. Van-de-sande, T. Gevers, and A. Smeulders, Selective Search for Object Recognition, International Journal of Computer Vision, vol.57, issue.1, 2004.
DOI : 10.1023/B:VISI.0000013087.49260.fb
URL : http://www.science.uva.nl/research/publications/2011/vandeSandeICCV2011/vandesande_iccv2011.pdf

D. Vazquez, A. M. Lopez, J. Marin, D. Ponsa, and D. Geronimo, Virtual and real world adaptation for pedestrian detection . Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.36, issue.4 2, pp.797-809, 2014.
DOI : 10.1109/tpami.2013.163

Y. Xiang, R. Mottaghi, and S. Savarese, Beyond PASCAL: A benchmark for 3D object detection in the wild, IEEE Winter Conference on Applications of Computer Vision, 2014.
DOI : 10.1109/WACV.2014.6836101

J. Xiao, B. Russell, and A. Torralba, Localizing 3D cuboids in single-view images, NIPS, 2012.

J. Yosinski, J. Clune, Y. Bengio, and H. Lipson, How transferable are features in deep neural networks?, Advances in Neural Information Processing Systems 27 (NIPS '14), pp.3320-3328, 2014.

M. Zia, M. Stark, B. Schiele, and K. Schindler, Detailed 3D Representations for Object Recognition and Modeling, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.35, issue.11
DOI : 10.1109/TPAMI.2013.87