Understanding deep learning techniques for recognition of human emotions using facial expressions: A comprehensive survey

M Karnati, A Seal, D Bhattacharjee… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Emotion recognition plays a significant role in cognitive psychology research. However,
measuring emotions is a challenging task. Thus, several approaches have been designed …

[HTML][HTML] A comprehensive survey on deep facial expression recognition: challenges, applications, and future guidelines

M Sajjad, FUM Ullah, M Ullah, G Christodoulou… - Alexandria Engineering …, 2023 - Elsevier
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 …

Cafe: Learning to condense dataset by aligning features

K Wang, B Zhao, X Peng, Z Zhu… - Proceedings of the …, 2022 - openaccess.thecvf.com
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 …

Learn from all: Erasing attention consistency for noisy label facial expression recognition

Y Zhang, C Wang, X Ling, W Deng - European Conference on Computer …, 2022 - Springer
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 …

Transfer: Learning relation-aware facial expression representations with transformers

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 …

Distract your attention: Multi-head cross attention network for facial expression recognition

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 …

Suppressing uncertainties for large-scale facial expression recognition

K Wang, X Peng, J Yang, S Lu… - Proceedings of the IEEE …, 2020 - openaccess.thecvf.com
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 …

Relative uncertainty learning for facial expression recognition

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 …

Facial expression recognition in the wild via deep attentive center loss

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 …

Dive into ambiguity: Latent distribution mining and pairwise uncertainty estimation for facial expression recognition

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 …