Face Mask

Face masks, ubiquitous during the COVID-19 pandemic, have become a significant research topic in computer vision, focusing on their impact on facial recognition and the development of robust detection and classification systems. Current research employs deep learning models, particularly convolutional neural networks (CNNs) like YOLOv5 and variations, and Vision Transformers (ViTs), to detect mask presence, classify mask type and proper usage, and even reconstruct masked faces. This work is crucial for applications ranging from public health monitoring and security systems to improving the accuracy and fairness of facial recognition technologies, addressing biases and limitations introduced by mask occlusion.