Face recognition technology is a biometric technology, which is based on the identification
of facial features of a person. People collect the face images, and the recognition equipment …

The replication crisis facing the psychological sciences is widely regarded as rooted in
methodological or statistical shortcomings. We argue that a large part of the problem is the …

Annotating a qualitative large-scale facial expression dataset is extremely difficult due to the
uncertainties caused by ambiguous facial expressions, low-quality facial images, and the …

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 …

Occlusion and pose variations, which can change facial appearance significantly, are two
major obstacles for automatic Facial Expression Recognition (FER). Though automatic FER …

The rapid development of computer vision makes human-computer interaction possible and
has a wide application prospect. Since the discovery of the first case of COVID-19, the global …

Automated affective computing in the wild setting is a challenging problem in computer
vision. Existing annotated databases of facial expressions in the wild are small and mostly …

Deep learning applies multiple processing layers to learn representations of data with
multiple levels of feature extraction. This emerging technique has reshaped the research …

Past research on facial expressions have used relatively limited datasets, which makes it
unclear whether current methods can be employed in real world. In this paper, we present a …

Automated Facial Expression Recognition (FER) has remained a challenging and
interesting problem in computer vision. Despite efforts made in developing various methods …