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Biometrics in the Time of Pandemic: 40% Masked Face Recognition Degradation can be Reduced to 2%. (arXiv:2201.00461v1 [cs.CV])
Jan. 4, 2022, 9:10 p.m. | Leonardo Queiroz, Kenneth Lai, Svetlana Yanushkevich, Vlad Shmerko
cs.CV updates on arXiv.org arxiv.org
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.
More from arxiv.org / cs.CV updates on arXiv.org
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