Facial Expression Recognition (FER) in the wild is extremely challenging due to occlusions,
variant head poses, face deformation and motion blur under unconstrained conditions …

Facial expression recognition (FER) becomes more challenging in the wild due to
unconstrained conditions, such as the different illumination, pose changes, and occlusion of …

Facial expression recognition (FER) in the wild unavoidably suffers from the effects of face
posture, illumination, and partial occlusion. In this article, we attempt to alleviate the above …

Facial expression recognition (FER) in the wild is considered to be one of the most
challenging tasks in computer vision because it requires identifying the categories of …

Aiming at the problem that face images are easily interfered by occlusion factors in
uncontrollable environments, and the complex structure of traditional convolutional neural …

Human ideas and sentiments are mirrored in facial expressions. Facial expression
recognition (FER) is a crucial type of visual data that can be utilized to deduce a person's …

Facial expression recognition (FER) has always been one of the key task in affective
computing. Over the years, researchers have worked to improve the performance of FER by …

Facial aging is widely used in criminal tracking and the search for lost children. If the aging
face is made up, it will greatly affect the discrimination of the tracking system. Therefore, the …

With recent developments in deep learning, facial expression manipulation (FEM) has
become one of the fields receiving great attention. However, many studies deal with learning …

Unsupervised Domain Adaptation has been an efficient approach to transferring the
semantic segmentation model across data distributions. Meanwhile, the recent Open …