Real-World Masked Face (口罩人脸数据集) dataset
Released: March 2020
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Real-World Masked Face Dataset is a dataset of photographs of over 5,000 masked faces of 525 people developed by researchers at Wuhan University.
In an accompanying research paper, the researchers say the project is to help identify individuals wearing face masks as a means of controlling the COVID-19 pandemic.
However, some commentators worry that the photos may be used for other purposes by the Chinese authorities, including the monitoring of Uyghurs in Xinjiang province.
The paper says the images are of 'public figures' gathered 'from massive internet resources.' The researchers have refused to discuss how they chose the people added to the dataset, or whether or not this may impact their privacy.
Dataset
Research, advocacy
Li X. (2022). Masked Face Detection and Calibration with Deep Learning Models (pdf)
Alturki R., Alharbi M., Ftoon AlAnzi F., Albahl S. (2022). Deep learning techniques for detecting and recognizing face masks: A survey
Khan J.Y., Al Alamin M.A. (2021). A Comparative Analysis of Machine Learning Approaches for Automated Face Mask Detection During COVID-19
Cabani A. et al (2021). MaskedFace-Net – A dataset of correctly/incorrectly masked face images in the context of COVID-19
Sharma V., Gangaraju S., Sharma V.K. (2021). Masked Face Recognition (pdf)
News, commentary, analysis
Page info
Type: Data
Published: January 2023