MFR 2021: Masked Face Recognition Competition
This addresses the problem of accurate face recognition for masked individuals, which is incremental as it builds on existing face recognition methods.
The paper summarizes the Masked Face Recognition Competition (MFR 2021), which aimed to improve face recognition accuracy for masked faces, with 10 out of 18 submitted solutions outperforming a top academic baseline in verification accuracy.
This paper presents a summary of the Masked Face Recognition Competitions (MFR) held within the 2021 International Joint Conference on Biometrics (IJCB 2021). The competition attracted a total of 10 participating teams with valid submissions. The affiliations of these teams are diverse and associated with academia and industry in nine different countries. These teams successfully submitted 18 valid solutions. The competition is designed to motivate solutions aiming at enhancing the face recognition accuracy of masked faces. Moreover, the competition considered the deployability of the proposed solutions by taking the compactness of the face recognition models into account. A private dataset representing a collaborative, multi-session, real masked, capture scenario is used to evaluate the submitted solutions. In comparison to one of the top-performing academic face recognition solutions, 10 out of the 18 submitted solutions did score higher masked face verification accuracy.