2020

Masked Face Recognition Dataset and Application

Wang, Zhongyuan, Wang, Guangcheng, Huang, Baojin et al.

Understand

In order to effectively prevent the spread of COVID-19 virus, almost everyone wears a mask during coronavirus epidemic.

This almost makes conventional facial recognition technology ineffective in many cases, such as community access control, face access control, facial attendance, facial security checks at train stations, etc.
Therefore, it is very urgent to improve the recognition performance of the existing face recognition technology on the masked faces.
Most current advanced face recognition approaches are designed based on deep learning, which depend on a large number of face samples.

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J. Deng, J. Guo, N. Xue, S. Zafeiriou, “ArcFace: Additive Angular Margin Loss for Deep Face Recognition,” in CVPR , Jun. 2019, pp. 4685-4694
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