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 …

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 …

Facial expression recognition (FER) has received increasing interest in computer vision. We
propose the TransFER model which can learn rich relation-aware local representations. It …

Due to the subjective annotation and the inherent inter-class similarity of facial expressions,
one of key challenges in Facial Expression Recognition (FER) is the annotation ambiguity …

Facial expression recognition (FER) in the wild received broad concerns in which occlusion
and pose variation are two key issues. This paper proposed a global multi-scale and local …

In this paper, we propose a novel Feature Decomposition and Reconstruction Learning
(FDRL) method for effective facial expression recognition. We view the expression …

Facial expression recognition is of significant importance in criminal investigation and digital
entertainment. Under unconstrained conditions, existing expression datasets are highly …

Facial Expression Recognition (FER) in the wild is an extremely challenging task. Recently,
some Vision Transformers (ViT) have been explored for FER, but most of them perform …

Facial expressions reflect people's feelings, emotions, and motives, attracting researchers to
develop a self-acting automatic facial expression recognition system. With the advances of …

Electroencephalography (EEG) provides access to neuronal dynamics non-invasively with
millisecond resolution, rendering it a viable method in neuroscience and healthcare …