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In this paper, we design a benchmark task and provide the associated datasets for recognizing face images and link them to corresponding entity keys in a knowledge base.
On spectral clustering: Analysis and an algorithm
Ng, A.Y., Jordan, M.I., Weiss, Y.: · 2001
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Semi-supervised learning using gaussian fields and harmonic functions
Zhu, X., Ghahramani, Z., Lafferty, J.: · 2003
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Semi-supervised learning on riemannian manifolds
Belkin, M., Niyogi, P.: · 2004
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Learning with local and global consistency
Zhou, D., Bousquet, O., Lal, T.N., Weston, J., Schölkopf, B.: · 2004
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Labeled faces in the wild: A database for studying face recognition in unconstrained environments
Huang, G.B., Ramesh, M., Berg, T., Learned-Miller, E.: · 2007
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Face recognition in unconstrained videos with matched background similarity
Wolf, L., Hassner, T., Maoz, I.: · 2011
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Imagenet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., Hinton, G.E.: · 2012
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Deepface: Closing the gap to human-level performance in face verification
Taigman, Y., Yang, M., Ranzato, M., Wolf, L.: · 2014
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Labeled faces in the wild: Updates and new reporting procedures
Huang, G.B., Learned-Miller, E.: · 2014
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DeepID3: Face recognition with very deep neural networks
Sun, Y., Wang, X., Tang, X.: · 2014
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Learning compact face representation: Packing a face into an int32
Fan, H., Yang, M., Cao, Z., Jiang, Y., Yin, Q.: · 2014
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A data-driven approach to cleaning large face datasets
Ng, H.W., Winkler, S.: · 2014
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An overview of research activities in facial age estimation using the FG-NET aging database
Panis, G., Lanitis, A.: · 2014
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Deep learning face representation from predicting 10,000 classes
Facenet: A unified embedding for face recognition and clustering
Schroff, F., Kalenichenko, D., Philbin, J.: · 2015
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Freebase data dumps
Google: · 2015
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ImageNet Large Scale Visual Recognition Challenge
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., Berg, A.C., Fei-Fei, L.: · 2015
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The MegaFace benchmark: 1 million faces for recognition at scale
Kemelmacher-Shlizerman, I., Seitz, S., Miller, D., Brossard, E.: · 2015
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Pushing the frontiers of unconstrained face detection and recognition: Iarpa janus benchmark a
Klare, B.F., Klein, B., Taborsky, E., Blanton, A., Cheney, J., Allen, K., Grother, P., Mah, A., Jain, A.K.: · 2015
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Deep face recognition
Parkhi, O.M., Vedaldi, A., Zisserman, A.: · 2015
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Sun, Y., Wang, X., Tang, X.: · 2014
Cited alongside, same era.
Learning face representation from scratch
Yi, D., Lei, Z., Liao, S., Li, S.Z.: · 2014
Cited alongside, same era.
Web-scale training for face identification
Taigman, Y., Yang, M., Ranzato, M., Wolf, L.: · 2015
Cited alongside, same era.
Later among the works it cites.
MS-Celeb-1M: Challenge of recognizing one million celebrities in the real world
Guo, Y., Zhang, L., Hu, Y., He, X., Gao, J.: · 2016
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