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 …

Abstract The Affective Behavior Analysis in-the-wild (ABAW2) 2021 Competition is the
second Competition-following the first very successful ABAW Competition held in …

Facial Expression Recognition (FER) is presently the aspect of cognitive and affective
computing with the most attention and popularity, aided by its vast application areas. Several …

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

This paper presents an efficiently robust facial expression recognition (FER) network, named
EfficientFace, which holds much fewer parameters but more robust to the FER in the wild …

Facial expression recognition has been an active area of research over the past few
decades, and it is still challenging due to the high intra-class variation. Traditional …

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 for emotion detection has always been an easy task for humans, but
achieving the same task with a computer algorithm is quite challenging. With the recent …

A facial expression is a combination of an expressive component and a neutral component
of a person. In this paper, we propose to recognize facial expressions by extracting …

Annotation errors and bias are inevitable among different facial expression datasets due to
the subjectiveness of annotating facial expressions. Ascribe to the inconsistent annotations …