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Despite significant recent advances in the field of face recognition, implementing face verification and recognition efficiently at scale presents serious challenges to current approaches.
Learning representations by back-propagating errors
D. E. Rumelhart, G. E. Hinton, and R. J. Williams · 1986
Earlier work this paper cites.
Backpropagation applied to handwritten zip code recognition
Y. LeCun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard, and L. D. Jackel · 1989
Earlier work this paper cites.
The CMU pose, illumination, and expression (PIE) database
T. Sim, S. Baker, and M. Bsat · 2002
Earlier work this paper cites.
The general inefficiency of batch training for gradient descent learning
D. R. Wilson and T. R. Martinez · 2003
Earlier work this paper cites.
Learning a distance metric from relative comparisons
M. Schultz and T. Joachims · 2004
Earlier work this paper cites.
Distance metric learning for large margin nearest neighbor classification
K. Q. Weinberger, J. Blitzer, and L. K. Saul · 2006
Earlier work this paper cites.
Labeled faces in the wild: A database for studying face recognition in unconstrained environments
G. B. Huang, M. Ramesh, T. Berg, and E. Learned-Miller · 2007
Earlier work this paper cites.
Curriculum learning
Y. Bengio, J. Louradour, R. Collobert, and J. Weston · 2009
Earlier work this paper cites.
Adaptive subgradient methods for online learning and stochastic optimization
J. Duchi, E. Hazan, and Y. Singer · 2011
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Face recognition in unconstrained videos with matched background similarity
L. Wolf, T. Hassner, and I. Maoz · 2011
Cited alongside, same era.
Bayesian face revisited: A joint formulation
D. Chen, X. Cao, L. Wang, F. Wen, and J. Sun · 2012
Cited alongside, same era.
Large scale distributed deep networks
J. Dean, G. Corrado, R. Monga, K. Chen, M. Devin, M. Mao, M. Ranzato, A. Senior, P. Tucker, K. Yang, Q. V. Le, and A. Y. Ng · 2012
Cited alongside, same era.
Maxout networks
I. J. Goodfellow, D. Warde-farley, M. Mirza, A. Courville, and Y. Bengio · 2013
Cited alongside, same era.
M. Lin, Q. Chen, and S. Yan · 2013
Surpassing human-level face verification performance on LFW with gaussianface
C. Lu and X. Tang · 2014
Later among the works it cites.
Deep learning face representation by joint identification-verification
Y. Sun, X. Wang, and X. Tang · 2014
Later among the works it cites.
Deeply learned face representations are sparse, selective, and robust
Y. Sun, X. Wang, and X. Tang · 2014
Later among the works it cites.
Going deeper with convolutions
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich · 2014
Later among the works it cites.
Deepface: Closing the gap to human-level performance in face verification
Y. Taigman, M. Yang, M. Ranzato, and L. Wolf · 2014
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Visualizing and understanding convolutional networks
M. D. Zeiler and R. Fergus · 2013
Cited alongside, same era.
Joint cascade face detection and alignment
D. Chen, S. Ren, Y. Wei, X. Cao, and J. Sun · 2014
Cited alongside, same era.
Later among the works it cites.
Learning fine-grained image similarity with deep ranking
J. Wang, Y. Song, T. Leung, C. Rosenberg, J. Wang, J. Philbin, B. Chen, and Y. Wu · 2014
Later among the works it cites.
Recover canonical-view faces in the wild with deep neural networks
Z. Zhu, P. Luo, X. Wang, and X. Tang · 2014
Later among the works it cites.