Abstract Context-Aware Emotion Recognition (CAER) is a crucial and challenging task that
aims to perceive the emotional states of the target person with contextual information …

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

Traditional techniques for emotion recognition have focused on the facial expression
analysis only, thus providing limited ability to encode context that comprehensively …

In the past three years, Emotion Recognition in the Wild (EmotiW) Grand Challenge has
drawn more and more attention due to its huge potential applications. In the fourth …

Human emotion recognition is an active research area in artificial intelligence and has made
substantial progress over the past few years. Many recent works mainly focus on facial …

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

Studies on emotion recognition (ER) show that combining lexical and acoustic information
results in more robust and accurate models. The majority of the studies focus on settings …

Temporal context is key to the recognition of expressions of emotion. Existing methods, that
rely on recurrent or self-attention models to enforce temporal consistency, work on the …

Emotion Recognition in Conversations (ERC) has gained increasing attention for
developing empathetic machines. Recently, many approaches have been devoted to …

Visual emotion recognition aims to associate images with appropriate emotions. There are
different visual stimuli that can affect human emotion from low-level to high-level, such as …