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Despite the large volume of face recognition datasets, there is a significant portion of subjects, of which the samples are insufficient and thus under-represented.
The MNIST database of handwritten digits
Y. LeCun, C. Cortes, and C. J.C. Burges · 1998
Earlier work this paper cites.
SMOTE: synthetic minority over-sampling technique
N. Chawla, K. Bowyer, L. Hall, and W. Kegelmeyer · 2002
Earlier work this paper cites.
Labeled faces in the wild: A database for studying face recognition in unconstrained environments
G. Huang, M. Ramesh, T. Berg, and E. Learned-Miller · 2007
Earlier work this paper cites.
Visualizing high-dimensional data using t-SNE
L. van der Maaten and G. Hinton · 2008
Earlier work this paper cites.
Learning from imbalanced data
H. He and E. A. Garcia · 2009
Earlier work this paper cites.
A survey on transfer learning
S. J. Pan and Q. Yang · 2009
Earlier work this paper cites.
Bayesian face revisited: A joint formulation
D. Chen, X. Cao, L. Wang, F. Wen, and J. Sun · 2012
Earlier work this paper cites.
ImageNet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. Hinton · 2012
Earlier work this paper cites.
Learning person-specific models for facial expression and action unit recognition
J. Chen, X. Liu, P. Tu, and A. Aragones · 2013
Earlier work this paper cites.
Transfer learning with one-class data
J. Chen and X. Liu · 2014
Earlier work this paper cites.
Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
Earlier work this paper cites.
Learning rich features from RGB-D images for object detection and segmentation
S. Gupta, R. Girshick, P. Arbelaez, and J. Malik · 2014
Earlier work this paper cites.
Deep learning face representation by joint identification-verification
Y. Sun, Y. Chen, X. Wang, and X. Tang · 2014
Earlier work this paper cites.
Learning face representation from scratch
D. Yi, Z. Lei, S. Liao, and S. Z. Li · 2014
Earlier work this paper cites.
Pushing the frontiers of unconstrained face detection and recognition: IARPA Janus Benchmark A
B. F. Klare, B. Klein, E. Taborsky, A. Blanton, J. Cheney, K. Allen, P. Grother, A. Mah, M. Burge, and A. K. Jain · 2015
Earlier work this paper cites.
Deep face recognition
O. Parkhi, A. Vedaldi, and A. Zisserman · 2015
Earlier work this paper cites.
ImageNet Large Scale Visual Recognition Challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. C. Berg, and L. Fei-Fei · 2015
Earlier work this paper cites.
FaceNet: A unified embedding for face recognition and clustering
F. Schroff, D. Kalenichenko, and J. Philbin · 2015
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A light CNN for deep face representation with noisy labels
X. Wu, R. He, Z. Sun, and T. Tan · 2015
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MS-Celeb-1M: A dataset and benchmark for large scale face recognition
Y. Guo, L. Zhang, Y. Hu, X. He, and J. Gao · 2016
Cited alongside, same era.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Cited alongside, same era.
Learning deep representation for imbalanced classification
C. Huang, Y. Li, C. C. Loy, and X. Tang · 2016
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Large-margin softmax loss for convolutional neural networks
W. Liu, Y. Wen, Z. Yu, and M. Yang · 2016
One-shot face recognition by promoting underrepresented classes
Y. Guo and L. Zhang · 2017
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Low-shot visual recognition by shrinking and hallucinating features
B. Hariharan and R. Girshick · 2017
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The inaturalist challenge 2017 dataset
G. V. Horn, O. M. Aodha, Y. Song, A. Shepard, H. Adam, P. Perona, and S. Belongie · 2017
Later among the works it cites.
The devial is in the tails: Fine-grained classification in the wild
G. V. Horn and P. Perona · 2017
Later among the works it cites.
SphereFace: Deep hypersphere embedding for face recognition
W. Liu, Y. Wen, Z. Yu, M. Li, B. Raj, and L. Song · 2017
Later among the works it cites.
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Pose-aware face recognition in the wild
I. Masi, S. Rawls, G. Medioni, and P. Natarajan · 2016
Cited alongside, same era.
Unsupervised representation learning with deep convolutional generative adversarial networks
A. Radford, L. Metz, and S. Chintala · 2016
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Triplet probabilistic embedding for face verification and clustering
S. Sankaranarayanan, A. Alavi, C. D. Castillo, and R. Chellappa · 2016
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Improved deep metric learning with multi-class n-pair loss objective
K. Sohn · 2016
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Matching networks for one shot learning
O. Vinyals, C. Blundell, T. Lillicrap, K. Kavukcuoglu, and D. Wierstra · 2016
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A discriminative feature learning approach for deep face recognition
Y. Wen, K. Zhang, Z. Li, and Y. Qiao · 2016
Cited alongside, same era.
E. Smirnov, A. Melnikov, S. Novoselov, E. Luckyanets, and G. Lavrentyeva · 2017
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Unsupervised domain adaptation for face recognition in unlabeled videos
K. Sohn, S. Liu, G. Zhong, X. Yu, M.-H. Yang, and M. Chandraker · 2017
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Disentangled representation learning GAN for pose-invariant face recognition
L. Tran, X. Yin, and X. Liu · 2017
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F. Wang, X. Xiang, J. Cheng, and A. L. Yuille · 2017
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Low-shot face recognition with hybrid classifiers
Y. Wu, H. Liu, and Y. Fu · 2017
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High performance large scale face recognition with multi-cognition softmax and feature retrieval
Y. Xu, Y. Cheng, J. Zhao, Z. Wang, L. Xiong, K. Jayashree, H. Tamura, T. Kagaya, S. Pranata, S. Shen, et al · 2017
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Neural aggregation network for video face recognition
J. Yang, P. Ren, D. Chen, F. Wen, H. Li, and G. Hua · 2017
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Towards large-pose face frontalization in the wild
X. Yin, X. Yu, K. Sohn, X. Liu, and M. Chandraker · 2017
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Range loss for deep face recognition with long-tailed training data
X. Zhang, Z. Fang, Y. Wen, Z. Li, and Y. Qiao · 2017
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CosFace: Large margin cosine loss for deep face recognition
H. Wang, Y. Wang, Z. Zhou, X. Ji, and W. Liu · 2018
Closest in time.
ArcFace: Additive angular margin loss for deep face recognition
J. Deng, J. Guo, N. Xue, and S. Zafeiriou · 2019
Closest in time.