The Mask-Obscured Face Dataset is a mask-obscured face detection and classification dataset collected during the COVID-19 pandemic.

Different from the face mask recognition (or detection) dataset, the mask face recognition sample set must contain multiple face images of the same person with and without masks. To this end, two mask face recognition sample sets were established.

(1) Real mask face recognition dataset: samples were collected from the Internet, sorted, cleaned and labeled. It contains 5,000 masked faces of 525 people and 90,000 normal faces.
(2) Simulated mask face recognition dataset: Masks are put on the faces in the public dataset to obtain a simulated mask face dataset of 10,000 people and 500,000 faces.

This dataset was released by the National Multimedia Software Engineering Technology Research Center of Wuhan University in March 2020, and the main publisher was Xiong Zhangyang.