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MFR 2021: Masked Face Recognition Competition

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 ; Ekenel, Hazim Kemal ; Kataoka, Asaki ; Ichikawa, Kohei ; Kubo, Shizuma ; Zhang, Jie ; He, Mingjie ; Han, Dan ; Shan, Shiguang ; Grm, Klemen ; Struc, Vitomir ; Seneviratne, Sachith ; Kasthuriarachchi, Nuran ; Rasnayaka, Sanka ; Neto, Pedro C. ; Sequeira, Ana F. ; Pinto, Joao Ribeiro ; Saffari, Mohsen ; Cardoso, Jaime S. (2021):
MFR 2021: Masked Face Recognition Competition.
IEEE, 2021 IEEE International Joint Conference on Biometrics (IJCB), virtual Conference, 04.-07.08.2021, ISBN 978-1-6654-3780-6,
DOI: 10.1109/IJCB52358.2021.9484337,
[Conference or Workshop Item]

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, multisession, real masked, capture scenario is used to evaluate the submitted solutions. In comparison to one of the topperforming academic face recognition solutions, 10 out of the 18 submitted solutions did score higher masked face verification accuracy.

Item Type: Conference or Workshop Item
Erschienen: 2021
Creators: 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 ; Ekenel, Hazim Kemal ; Kataoka, Asaki ; Ichikawa, Kohei ; Kubo, Shizuma ; Zhang, Jie ; He, Mingjie ; Han, Dan ; Shan, Shiguang ; Grm, Klemen ; Struc, Vitomir ; Seneviratne, Sachith ; Kasthuriarachchi, Nuran ; Rasnayaka, Sanka ; Neto, Pedro C. ; Sequeira, Ana F. ; Pinto, Joao Ribeiro ; Saffari, Mohsen ; Cardoso, Jaime S.
Title: MFR 2021: Masked Face Recognition Competition
Language: English
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, multisession, real masked, capture scenario is used to evaluate the submitted solutions. In comparison to one of the topperforming academic face recognition solutions, 10 out of the 18 submitted solutions did score higher masked face verification accuracy.

Publisher: IEEE
ISBN: 978-1-6654-3780-6
Uncontrolled Keywords: Biometrics, Deep learning, Machine learning, Face recognition, Artificial neural networks
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
20 Department of Computer Science > Mathematical and Applied Visual Computing
Event Title: 2021 IEEE International Joint Conference on Biometrics (IJCB)
Event Location: virtual Conference
Event Dates: 04.-07.08.2021
Date Deposited: 03 Aug 2021 13:11
DOI: 10.1109/IJCB52358.2021.9484337
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