Automatic emotion recognition is an active research topic with wide range of applications.
Due to the high manual annotation cost and inevitable label ambiguity, the development of …

Emotion recognition is involved in several real-world applications. With an increase in
available modalities, automatic understanding of emotions is being performed more …

Multimodal emotion recognition study is hindered by the lack of labelled corpora in terms of
scale and diversity, due to the high annotation cost and label ambiguity. In this paper, we …

Despite the recent achievements made in the multi-modal emotion recognition task, two
problems still exist and have not been well investigated: 1) the relationship between different …

Emotion Recognition is a challenging research area given its complex nature, and humans
express emotional cues across various modalities such as language, facial expressions …

Multi-modal emotion recognition aims to extract sentiment-related information from multiple
sources and integrate different modal representations for sentiment analysis. Alignment is …

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

Multi-modal emotion recognition has gained increasing attention in recent years due to its
widespread applications and the advances in multi-modal learning approaches. However …

Despite remarkable advances in emotion recognition, they are severely restrained from
either the essentially limited property of the employed single modality, or the synchronous …

State-of-the-art approaches for the previous emotion recognition in the wild challenges are
usually built on prevailing Convolutional Neural Networks (CNNs). Although there is clear …