Face Image Quality Assessment

Face image quality assessment (FIQA) aims to automatically determine how suitable a face image is for applications like facial recognition, focusing on factors impacting recognition accuracy. Current research emphasizes developing FIQA methods robust to variations in face alignment and ethnicity, often employing deep learning models such as Generative Adversarial Networks (GANs) and knowledge distillation techniques to improve accuracy and reduce bias. These advancements are crucial for enhancing the reliability and fairness of facial recognition systems and other applications relying on the quality of face images.