FER-EMFormer: An enhanced mamba-transformer network for facial expression recognition

Abstract Facial expression recognition (FER) has a variety of applications in advanced intelligent fields such as human–computer interaction, cognitive psychology, and intelligent driving. However, FER in wild scenarios faces multiple challenges, including occlusion, pose variations, and subtle differences, which make current models unable to address these issues effectively. To tackle these challenges, we propose an efficient and robust Enhanced Mamba-Transformer architecture for FER (FER-EMFor