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Modern Face Recognition using New Masked Face Dataset Generated by Deep Learning

딥러닝 기반의 새로운 마스크 얼굴 데이터 세트를 사용한 최신 얼굴 인식

  • Pann, Vandet (Division of Computer Science and Engineering, Jeonbuk National University) ;
  • Lee, Hyo Jong (Division of Computer Science and Engineering, Jeonbuk National University)
  • 판반뎃 (전북대학교 컴퓨터공학부) ;
  • 이효종 (전북대학교 컴퓨터공학부)
  • Published : 2021.11.04

Abstract

The most powerful and modern face recognition techniques are using deep learning methods that have provided impressive performance. The outbreak of COVID-19 pneumonia has spread worldwide, and people have begun to wear a face mask to prevent the spread of the virus, which has led existing face recognition methods to fail to identify people. Mainly, it pushes masked face recognition has become one of the most challenging problems in the face recognition domain. However, deep learning methods require numerous data samples, and it is challenging to find benchmarks of masked face datasets available to the public. In this work, we develop a new simulated masked face dataset that we can use for masked face recognition tasks. To evaluate the usability of the proposed dataset, we also retrained the dataset with ArcFace based system, which is one the most popular state-of-the-art face recognition methods.

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Acknowledgement

This research was supported by Basic Science Research Program through the NRF of Korea funded by the Ministry of Education (GR 2019R1D1A3A03103736).