Emotion recognition plays a significant role in cognitive psychology research. However,
measuring emotions is a challenging task. Thus, several approaches have been designed …

The POSTER has achieved SOTA performance in facial expression recognition (FER) by
effectively combining facial landmarks and image features through its two-stream pyramid …

Dataset condensation aims at reducing the network training effort through condensing a
cumbersome training set into a compact synthetic one. State-of-the-art approaches largely …

Abstract Noisy label Facial Expression Recognition (FER) is more challenging than
traditional noisy label classification tasks due to the inter-class similarity and the annotation …

This paper presents a novel facial expression recognition network, called Distract your
Attention Network (DAN). Our method is based on two key observations in biological visual …

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 …

The key challenge of zero-shot learning (ZSL) is how to infer the latent semantic knowledge
between visual and attribute features on seen classes, and thus achieving a desirable …

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 …

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 …

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 …