Depression stands as one of the most widespread psychological disorders and has
garnered increasing attention. Currently, how to effectively achieve automatic multimodal …

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

The dramatic impact of the COVID-19 pandemic has resulted in the closure of physical
classrooms and teaching methods being shifted to the online medium. To make the online …

Physiological studies have shown that there are some differences in speech and facial
activities between depressive and healthy individuals. Based on this fact, we propose a …

Music videos contain a great deal of visual and acoustic information. Each information
source within a music video influences the emotions conveyed through the audio and video …

Recent deep neural networks based methods have achieved state-of-the-art performance
on various facial expression recognition tasks. Despite such progress, previous researches …

Visual emotion analysis (VEA) has attracted great attention recently, due to the increasing
tendency of expressing and understanding emotions through images on social networks …

In recent years, research has found that the impact of depression status primarily lies in
patients' language expression and facial expressions. Furthermore, facial expressions and …

Continuous dimensional emotion recognition for facial video sequence is a crucial and
challenging task in Affective Computing and Human-Computer Intelligent Interaction. The …

Video-based dimensional emotion recognition aims to map human affect into the
dimensional emotion space based on visual signals, which is a fundamental challenge in …