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Masked Face Recognition Challenge: The WebFace260M Track Report by Zhu, Zheng; Huang, Guan; Deng, Jiankang; Ye, Yun; Huang, Junjie; Chen, Xinze; Zhu, Jiagang; Yang, Tian; Guo, Jia; Lu, Jiwen; Du, Dalong; Zhou, Jie is a scholarly article available to read on EtoBox.

What is Masked Face Recognition Challenge: The WebFace260M Track Report about?

According to WHO statistics, there are more than 204,617,027 confirmed COVID-19 cases including 4,323,247 deaths worldwide till August 12, 2021. During the coronavirus epidemic, almost everyone wears a facial mask. Traditionally, face recognition approaches process mostly non-occluded faces, which include primary facial features such as the eyes, nose, and mouth. Removing the mask for authentication in airports or laboratories will increase the risk of virus infection, posing a huge challenge to current face recognition systems. Due to the sudden outbreak of the epidemic, there are yet no publicly available real-world masked face recognition (MFR) benchmark. To cope with the above-mentioned issue, we organize the Face Bio-metrics under COVID Workshop and Masked Face Recognition Challenge in ICCV 2021. Enabled by the ultra-large-scale WebFace260M benchmark and the Face Recognition Under Inference Time conStraint (FRUITS) protocol, this challenge (WebFace260M Track) aims to push the frontiers of practical MFR. Since public evaluation sets are mostly saturated or contain noise, a new test set is gathered consisting of elaborated 2,478 celebrities and 60,926 faces. Meanwhile, we collec

Author

Zhu, Zheng; Huang, Guan; Deng, Jiankang; Ye, Yun; Huang, Junjie; Chen, Xinze; Zhu, Jiagang; Yang, Tian; Guo, Jia; Lu, Jiwen; Du, Dalong; Zhou, Jie

Published

2021

Language

EN