Masked Face Analysis via Multi-Task Deep Learning

Vatsa S. Patel, Zhongliang Nie, Trung-Nghia Le, Tam V. Nguyen
2021 Journal of Imaging  
Face recognition with wearable items has been a challenging task in computer vision and involves the problem of identifying humans wearing a face mask. Masked face analysis via multi-task learning could effectively improve performance in many fields of face analysis. In this paper, we propose a unified framework for predicting the age, gender, and emotions of people wearing face masks. We first construct FGNET-MASK, a masked face dataset for the problem. Then, we propose a multi-task deep
more » ... ng model to tackle the problem. In particular, the multi-task deep learning model takes the data as inputs and shares their weight to yield predictions of age, expression, and gender for the masked face. Through extensive experiments, the proposed framework has been found to provide a better performance than other existing methods.
doi:10.3390/jimaging7100204 pmid:34677290 pmcid:PMC8539947 fatcat:qd663hk45zdxnowvbe7unedj6m