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This paper presents an end-to-end convolutional neural network (CNN) for 2D-3D exemplar detection.
Machine perception of 3-D solids
L. Roberts · 1965
Earlier work this paper cites.
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Y. LeCun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard, and L. D. Jackel · 1989
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M. Irani and P. Anandan · 1998
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Object recognition in the geometric era: A retrospective
J. L. Mundy · 2006
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Earlier work this paper cites.
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Earlier work this paper cites.
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Y. Bengio · 2012
Earlier work this paper cites.
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S. Fidler, S. Dickinson, and R. Urtasun · 2012
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Analyzing 3D objects in cluttered images
M. Hejrati and D. Ramanan · 2012
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A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
Earlier work this paper cites.
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T. Chen, Z. Zhu, A. Shamir, S.-M. Hu, and D. Cohen-Or · 2013
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J. J. Lim, H. Pirsiavash, and A. Torralba · 2013
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Virtual and real world adaptation for pedestrian detection
D. Vazquez, A. M. Lopez, J. Marin, D. Ponsa, and D. Geronimo · 2014
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Beyond PASCAL: A Benchmark for 3D Object Detection in the Wild
Y. Xiang, R. Mottaghi, and S. Savarese · 2014
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How transferable are features in deep neural networks?
J. Yosinski, J. Clune, Y. Bengio, and H. Lipson · 2014
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Understanding deep features with computer-generated imagery
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