2014

Learning Face Representation from Scratch

Yi, Dong, Lei, Zhen, Liao, Shengcai et al.

Understand

Pushing by big data and deep convolutional neural network (CNN), the performance of face recognition is becoming comparable to human.

Using private large scale training datasets, several groups achieve very high performance on LFW, i.e., 97% to 99%.
While there are many open source implementations of CNN, none of large scale face dataset is publicly available.
The current situation in the field of face recognition is that data is more important than algorithm.

Built on

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M. A. Turk and A. P. Pentland · 1991
Earlier work this paper cites.
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“The FERET evaluation methodology for face-recognition algorithms”
P. J. Phillips, H. Moon, S. A. Rizvi, and P. J. Rauss · 2000
Earlier work this paper cites.
“Gabor feature based classification using the enhanced fisher linear discriminant model for face recognition”
C. Liu and H. Wechsler · 2002
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.
“Labeled faces in the wild: A database for studying face recognition in unconstrained environments”
G. B. Huang, M. Mattar, T. Berg, and E. Learned-Miller · 2007
Earlier work this paper cites.
“Illumination invariant face recognition using near-infrared images”
S. Z. Li, R. Chu, S. Liao, and L. Zhang · 2007
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“Learning deep architectures for AI”
Y. Bengio · 2009
Earlier work this paper cites.

Similar

Attribute and simile classifiers for face verification
N. Kumar, A. C. Berg, P. N. Belhumeur, and S. K. Nayar · 2009
Cited alongside, same era.
“Rectified linear units improve restricted boltzmann machines”
V. Nair and G. E. Hinton · 2010
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“Face recognition by exploring information jointly in space, scale and orientation”
Z. Lei, S. Liao, M. Pietikainen, and S. Z. Li · 2011
Cited alongside, same era.
“Face recognition with decision tree-based local binary patterns”
D. Maturana, D. Mery, and A. Soto · 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.
“Improving neural networks by preventing co-adaptation of feature detectors”
Original
G. E. Hinton, N. Srivastava, A. Krizhevsky, I. Sutskever, and R. R. Salakhutdinov · 2012
Cited alongside, same era.
“Imagenet classification with deep convolutional neural networks”
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
Cited alongside, same era.
“Blessing of dimensionality: High-dimensional feature and its efficient compression for face verification”
D. Chen, X. Cao, F. Wen, and J. Sun · 2013
Cited alongside, same era.
cuda-convnet
A. Krizhevsky
Cited in the paper.
“Benchmark of large-scale unconstrained face recognition”
S. Liao
Cited in the paper.

Then

“Learning discriminant face descriptor”
Z. Lei, M. Pietikainen, and S. Li · 2013
Later among the works it cites.
“Towards pose robust face recognition”
D. Yi, Z. Lei, and S. Z. Li · 2013
Later among the works it cites.
“Cross-age reference coding for age-invariant face recognition and retrieval”
B.-C. Chen, C.-S. Chen, and W. H. Hsu · 2014
Closest in time.
“A benchmark study of large-scale unconstrained face recognition”
S. Liao, Z. Lei, D. Yi, and S. Z. Li · 2014
Closest in time.
“Very deep convolutional networks for large-scale image recognition”
Original
K. Simonyan and A. Zisserman · 2014
Closest in time.
“Deep learning face representation by joint identification-verification”
Original
Y. Sun, X. Wang, and X. Tang · 2014
Closest in time.
“Going deeper with convolutions”
Original
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich · 2014
Closest in time.
“Deepface: Closing the gap to human-level performance in face verification”
Y. Taigman, M. Yang, M. Ranzato, and L. Wolf · 2014
Closest in time.

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