Towards Large-scale Masked Face Recognition

• URL: http://arxiv.org/abs/2310.16364v1
• Date: Wed, 25 Oct 2023 05:04:47 GMT
• Title: Towards Large-scale Masked Face Recognition
• Authors: Manyuan Zhang, Bingqi Ma, Guanglu Song, Yunxiao Wang, Hongsheng Li, Yu Liu
• Abstract summary: During the COVID-19 coronavirus epidemic, almost everyone is wearing masks, which poses a huge challenge for deep learning-based face recognition algorithms. In this paper, we will present our textbfchampionship solutions in ICCV MFR WebFace260M and InsightFace unconstrained tracks.
• Score: 44.380235958577785
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: During the COVID-19 coronavirus epidemic, almost everyone is wearing masks, which poses a huge challenge for deep learning-based face recognition algorithms. In this paper, we will present our \textbf{championship} solutions in ICCV MFR WebFace260M and InsightFace unconstrained tracks. We will focus on four challenges in large-scale masked face recognition, i.e., super-large scale training, data noise handling, masked and non-masked face recognition accuracy balancing, and how to design inference-friendly model architecture. We hope that the discussion on these four aspects can guide future research towards more robust masked face recognition systems.

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