Affective computing conjoins the research topics of emotion recognition and sentiment
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …

Emotion recognition plays a significant role in cognitive psychology research. However,
measuring emotions is a challenging task. Thus, several approaches have been designed …

Facial Expression Recognition (FER) in the wild is extremely challenging due to occlusions,
variant head poses, face deformation and motion blur under unconstrained conditions …

This paper proposes a dynamic facial expression recognition transformer (Former-DFER) for
the in-the-wild scenario. Specifically, the proposed Former-DFER mainly consists of a …

Affective computing is one of the most important research fields in modern human–computer
interaction (HCI). The goal of affective computing is to study and develop the theories …

Despite substantial progress in Facial Expression Recognition (FER) in recent decades,
most previous methods have been developed to recognize constrained facial expressions …

An image is worth a thousand words; hence, a face image illustrates extensive details about
the specification, gender, age, and emotional states of mind. Facial expressions play an …

Emotion recognition has opened up many challenges, which lead to various advances in
computer vision and artificial intelligence. The rapid development in this field has …

Recent research has shown that facial expressions and body gestures are two significant
implications in identifying human emotions. However, these studies mainly focus on …

Facial Expression Recognition (FER) can be widely applied to various research areas, such
as mental diseases diagnosis and human social/physiological interaction detection. With the …