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In this paper, we introduce a new large-scale face dataset named VGGFace2.
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
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Face recognition in unconstrained videos with matched background similarity
L. Wolf, T. Hassner, and I. Maoz · 2011
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Aggregating local image descriptors into compact codes
H. Jegou, F. Perronnin, M. Douze, J. Sánchez, P. Perez, and C. Schmid · 2012
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All about VLAD
R. Arandjelović and A. Zisserman · 2013
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A data-driven approach to cleaning large face datasets
H.-W. Ng and S. Winkler · 2014
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An overview of research activities in facial age estimation using the fg-net aging database
G. Panis and A. Lanitis · 2014
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Deep learning face representation from predicting 10,000 classes
Y. Sun, X. Wang, and X. Tang · 2014
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Learning face representation from scratch
D. Yi, Z. Lei, S. Liao, and S. Z. Li · 2014
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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, and A. K. Jain · 2015
Cited alongside, same era.
Deep face recognition
O. M. Parkhi, A. Vedaldi, and A. Zisserman · 2015
Cited alongside, same era.
Dex: Deep expectation of apparent age from a single image
R. Rothe, R. Timofte, and L. Van Gool · 2015
Cited alongside, same era.
Facenet: A unified embedding for face recognition and clustering
F. Schroff, D. Kalenichenko, and J. Philbin · 2015
Cited alongside, same era.
Web-scale training for face identification
Y. Taigman, M. Yang, M. Ranzato, and L. Wolf · 2015
Cited alongside, same era.
Umdfaces: An annotated face dataset for training deep networks
The megaface benchmark: 1 million faces for recognition at scale
I. Kemelmacher-Shlizerman, S. M. Seitz, D. Miller, and E. Brossard · 2016
Later among the works it cites.
Joint face detection and alignment using multitask cascaded convolutional networks
K. Zhang, Z. Zhang, Z. Li, and Y. Qiao · 2016
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The do’s and don’ts for cnn-based face verification
A. Bansal, C. Castillo, R. Ranjan, and R. Chellappa · 2017
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Template adaptation for face verification and identification
N. Crosswhite, J. Byrne, C. Stauffer, O. Parkhi, Q. Cao, and A. Zisserman · 2017
Closest in time.
Squeeze-and-Excitation networks
J. Hu, L. Shen, and G. Sun · 2017
Closest in time.
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A. Bansal, A. Nanduri, C. Castillo, R. Ranjan, and R. Chellappa · 2016
Cited alongside, same era.
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.
Dbpedia. http://wiki.dbpedia.org/
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Freebase. http://www.freebase.com/
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K. Sohn, S. Liu, G. Zhong, X. Yu, M.-H. Yang, and M. Chandraker · 2017
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Iarpa janus benchmark-b face dataset
C. Whitelam, E. Taborsky, A. Blanton, B. Maze, J. Adams, T. Miller, N. Kalka, A. K. Jain, J. A. Duncan, K. Allen, et al · 2017
Closest in time.
Neural aggregation network for video face recognition
J. Yang, P. Ren, D. Zhang, D. Chen, F. Wen, H. Li, and G. Hua · 2017
Closest in time.