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Biometrics in the Time of Pandemic: 40% Masked Face Recognition Degradation can be Reduced to 2%

2022-01-03 03:17:06
Leonardo Queiroz, Kenneth Lai, Svetlana Yanushkevich, Vlad Shmerko
arXiv_AI
         
Abstract

In this study of the face recognition on masked versus unmasked faces generated using Flickr-Faces-HQ and SpeakingFaces datasets, we report 36.78% degradation of recognition performance caused by the mask-wearing at the time of pandemics, in particular, in border checkpoint scenarios. We have achieved better performance and reduced the degradation to 1.79% using advanced deep learning approaches in the cross-spectral domain.

Abstract (translated)

URL

https://arxiv.org/abs/2201.00461

PDF

https://arxiv.org/pdf/2201.00461.pdf

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