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MFR 2021: Masked Face Recognition Competition

Authors :
Boutros, Fadi
Damer, Naser
Kolf, Jan Niklas
Raja, Kiran
Kirchbuchner, Florian
Ramachandra, Raghavendra
Kuijper, Arjan
Fang, Pengcheng
Zhang, Chao
Wang, Fei
Montero, David
Aginako, Naiara
Sierra, Basilio
Nieto, Marcos
Erakin, Mustafa Ekrem
Demir, Ugur
Kemal, Hazim
Ekenel
Kataoka, Asaki
Ichikawa, Kohei
Kubo, Shizuma
Zhang, Jie
He, Mingjie
Han, Dan
Shan, Shiguang
Grm, Klemen
Štruc, Vitomir
Seneviratne, Sachith
Kasthuriarachchi, Nuran
Rasnayaka, Sanka
Neto, Pedro C.
Sequeira, Ana F.
Pinto, Joao Ribeiro
Saffari, Mohsen
Cardoso, Jaime S.
Publication Year :
2021

Abstract

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.<br />Comment: Accepted at International Join Conference on Biometrics (IJCB 2021)

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2106.15288
Document Type :
Working Paper