The existing masked face recognition algorithms almost tend to adopt synthetic masked face
datasets for training. However, these models are limited as they rely on existing mask …

Face recognition has been one of the most popular applications in the field of target
detection. Currently, frontal faces can be easily detected, but multi-view face detection …

In recent years, advances in deep learning (DL) techniques for video analysis have
developed to solve the problem of real-time processing. Automated face recognition in the …

Face recognition models often encounter various unseen domains and environments in real-
world applications, leading to unsatisfactory performance due to the open-set nature of face …

No-reference image quality assessment (NR-IQA) methods, inspired by the free energy
principle, improve the accuracy of image quality prediction by simulating the human brain's …

During the COVID-19 coronavirus epidemic, almost everyone wears a facial mask, which
poses a huge challenge for face recognition. Therefore, it is urgent to improve the …

Facial expression recognition plays a crucial role in human-computer intelligent interaction.
Due to the problem of missing facial information caused by face masks, the average …

Image quality assessment (IQA) is an important problem in computer vision with many
applications. We propose a transformer-based multi-task learning framework for the IQA …

To address the problem of reduced face recognition accuracy in masked scenarios, this
paper proposes a masked face reconstruction algorithm DeMaskGAN, which uses the …