%0 Journal Article %A WANG Xinran %A TIAN Qichuan %A ZHANG Dong %T Review of Research on Face Mask Wearing Detection %D 2022 %R 10.3778/j.issn.1002-8331.2110-0396 %J Computer Engineering and Applications %P 13-26 %V 58 %N 10 %X Face mask wearing detection is an emerging research topic that has developed rapidly in the past two years in the context of the global COVID-19 epidemic. Under regular epidemic situation, wearing masks is an important means of effective epidemic prevention, therefore it is essential to remind and check people whether to wear masks in public places. Using artificial intelligence to complete mask wearing detection can achieve the purpose of real-time supervision, save human resources and effectively avoid mistakes, missed detection and other problems. The models and relevant algorithms used in current mask wearing detection research are reviewed. Firstly, the task and application background of mask wearing detection are described. Then, the detection algorithms based on deep neural networks and object detection models are summarized and  analyzed, the advantages and disadvantages, improvement methods and application scenarios of different research schemes are discussed. Secondly, common related data sets are introduced, and the detection performance of each algorithm is compared. Finally, the existing problems and the direction of future development are discussed and prospected. %U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.2110-0396