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 1 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 [38]. 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.