Few-shot learning for facial expression recognition: a comprehensive survey

Abstract Facial expression recognition (FER) is utilized in various fields that analyze facial expressions. FER attracting increasing attention for its role improving the convenience human life. It widely applied human–computer interaction tasks. However, recently, tasks have encountered certain data and training issues. To address these issues FER, few-shot learning (FSL) has been researched as a new approach. In this paper, we focus on analyzing techniques based FSL consider computational complexity processing time models. it can solve problems of with few datasets generalizing wild-environmental condition. Based our analysis, describe existing challenges use systems suggest research directions to resolve using be efficient reduce many other real-time an important area further research.