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arXiv:2108.08191 (cs)
COVID-19 e-print

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[Submitted on 18 Aug 2021]

Title:Masked Face Recognition Challenge: The InsightFace Track Report

Authors:Jiankang Deng, Jia Guo, Xiang An, Zheng Zhu, Stefanos Zafeiriou
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Abstract:During the COVID-19 coronavirus epidemic, almost everyone wears a facial mask, which poses a huge challenge to deep face recognition. In this workshop, we organize Masked Face Recognition (MFR) challenge and focus on bench-marking deep face recognition methods under the existence of facial masks. In the MFR challenge, there are two main tracks: the InsightFace track and the WebFace260M track. For the InsightFace track, we manually collect a large-scale masked face test set with 7K identities. In addition, we also collect a children test set including 14K identities and a multi-racial test set containing 242K identities. By using these three test sets, we build up an online model testing system, which can give a comprehensive evaluation of face recognition models. To avoid data privacy problems, no test image is released to the public. As the challenge is still under-going, we will keep on updating the top-ranked solutions as well as this report on the arxiv.
Comments: The WebFace260M Track of ICCV-21 MFR Challenge is still open in this https URL
Subjects: Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2108.08191 [cs.CV]
  (or arXiv:2108.08191v1 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.2108.08191

Submission history

From: Zheng Zhu [view email]
[v1] Wed, 18 Aug 2021 15:14:44 UTC (676 KB)
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