A Multiscale Network with Supervised Contrastive Learning for Real-Time Facial Emotion Recognition

ArXi:2606.01069v1 Announce Type: new Real-time emotion recognition from facial expressions is a challenging task, particularly in video-based scenarios where multiple emotional states may occur over time. The difficulty increases further due to the fact that each emotional state is associated with facial expressions that vary significantly across individuals. The change of facial expressions portraying emotional state is not discrete, but rather continuous, which is very challenging to represent through computational aids.