Masked Face Recognition based on Attention Mechanism and FaceX-Zoo
2021 International Conference on Digital Society and Intelligent Systems, DSInS 2021
; : 107-110, 2021.
Article
in English
| Scopus | ID: covidwho-1713982
ABSTRACT
Recently, due to the outbreak of the COVID-19 epidemic in the world, wearing face masks has become a trend, which brings difficulties to the traditional face recognition technologies that do not actively focus on the upper part of the face. This paper proposes a novel method for masked face recognition based on attention mechanism and FaceX-Zoo (an open-source method of JD.COM). In order to make the module focus on the regions around the eyes, we integrated the CBAM (Convolutional Block Attention Module) attention mechanism into ResNet50 and MobileFaceNet network. Furthermore, the FaceX-Zoo method was used to generate masked face images to improve the module performance. Experiment results show that the proposed approach can improve the performance of masked face recognition compared with competitive approaches. © 2021 IEEE.
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Databases of international organizations
Database:
Scopus
Language:
English
Journal:
2021 International Conference on Digital Society and Intelligent Systems, DSInS 2021
Year:
2021
Document Type:
Article
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