Mask-wearing recognition in the wild
Yan Wang, Xiubao ZHANG, Jieping YE, Haifeng SHEN, Ziyuan LIN, Wanxin Tian · Scientia Sinica Informationis · 2020
For public health and safety, wearing of masks is one of the most significant means to prevent infections. Additionally, masks protect employees of heavy industry from certain diseases during manufacture. To meet the demand of automatic mask-wearing recognition in scenes of life, we propose a recognition algorithm based on face detection and face attribute recognition. The face detection model not only adopted a fused feature pyramid and a spatial and channel attention mechanism but also a segmentation branch for weak supervision learning. Then for the detected face, we used classification for fast recognition. Moreover, we employed nearly 200000 images, attention mechanisms, data augmentation, and other techniques to enhance the robustness. Besides, this technology has been widely used in Didi Chuxing's inspection systems and achieves 99.50% accuracy. Importantly, both the service and key algorithms have been opened to the public to maximize their social and application value.