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 …
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 …
F Xue, Q Wang, G Guo - Proceedings of the IEEE/CVF …, 2021 - openaccess.thecvf.com
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 …
Z Wen, W Lin, T Wang, G Xu - Biomimetics, 2023 - mdpi.com
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 …
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 …
Y Zhang, C Wang, W Deng - Advances in Neural …, 2021 - proceedings.neurips.cc
In facial expression recognition (FER), the uncertainties introduced by inherent noises like ambiguous facial expressions and inconsistent labels raise concerns about the credibility of …
AH Farzaneh, X Qi - Proceedings of the IEEE/CVF winter …, 2021 - openaccess.thecvf.com
Learning discriminative features for Facial Expression Recognition (FER) in the wild using Convolutional Neural Networks (CNNs) is a non-trivial task due to the significant intra-class …
J She, Y Hu, H Shi, J Wang… - Proceedings of the …, 2021 - openaccess.thecvf.com
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 …