Emotion recognition is the ability to precisely infer human emotions from numerous sources
and modalities using questionnaires, physical signals, and physiological signals. Recently …

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 has recently attracted extensive interest due to its significant
applications to human–computer interaction. The expression of human emotion depends on …

Facial expression recognition (FER) is an emerging and multifaceted research topic.
Applications of FER in healthcare, security, safe driving, and so forth have contributed to the …

With the transition of facial expression recognition (FER) from laboratory-controlled to
challenging in-the-wild conditions and the recent success of deep learning techniques in …

Many existing studies reveal that annotation inconsistency widely exists among a variety of
facial expression recognition (FER) datasets. The reason might be the subjectivity of human …

The three-dimensional convolutional neural network (3D-CNN) and long short-term memory
(LSTM) have consistently outperformed many approaches in video-based facial expression …

Facial emotion recognition (FER) is a computer vision process aimed at detecting and
classifying human emotional expressions. FER systems are currently used in a vast range of …

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 …

Although Transformer can be powerful for modeling visual relations and describing
complicated patterns, it could still perform unsatisfactorily for video-based facial expression …