The emergence of artificial emotional intelligence technology is revolutionizing the fields of
computers and robotics, allowing for a new level of communication and understanding of …

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 …

Multimodal emotion recognition aims to identify human emotions from text, audio, and visual
modalities. Previous methods either explore correlations between different modalities or …

Understanding emotion in context is a rising hotspot in the computer vision community.
Existing methods lack reliable context semantics to mitigate uncertainty in expressing …

Context-aware emotion recognition (CAER) has recently boosted the practical applications
of affective computing techniques in unconstrained environments. Mainstream CAER …

Dynamic expression recognition in the wild is a challenging task due to various obstacles,
including low light condition, non-positive face, and face occlusion. Purely vision-based …

Expert systems are being extensively used to make critical decisions involving emotional
analysis in affective computing. The evolution of deep learning algorithms has improved the …

For a better intention inference, we often try to figure out the emotional states of other people
in social communications. Many studies on affective computing have been carried out to …

Cross-modal hashing is a hot issue in the multimedia community, which is to generate
compact hash code from multimedia content for efficient cross-modal search. Two …

Emotion recognition is a fundamental aspect of human communication and plays a crucial
role in various domains. This project aims at developing an efficient model for real-time …