Deep facial expression recognition: A survey

S Li, W Deng - IEEE transactions on affective computing, 2020 - ieeexplore.ieee.org
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 …

Generative adversarial networks: A survey toward private and secure applications

Z Cai, Z **ong, H Xu, P Wang, W Li, Y Pan - ACM Computing Surveys …, 2021 - dl.acm.org
Generative Adversarial Networks (GANs) have promoted a variety of applications in
computer vision and natural language processing, among others, due to its generative …

Generative adversarial networks for face generation: A survey

A Kammoun, R Slama, H Tabia, T Ouni… - ACM Computing …, 2022 - dl.acm.org
Recently, generative adversarial networks (GANs) have progressed enormously, which
makes them able to learn complex data distributions in particular faces. More and more …

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 …

Review of studies on emotion recognition and judgment based on physiological signals

W Lin, C Li - Applied Sciences, 2023 - mdpi.com
People's emotions play an important part in our daily life and can not only reflect
psychological and physical states, but also play a vital role in people's communication …

Facial expression recognition: A survey

Y Huang, F Chen, S Lv, X Wang - Symmetry, 2019 - mdpi.com
Facial Expression Recognition (FER), as the primary processing method for non-verbal
intentions, is an important and promising field of computer vision and artificial intelligence …

SensitiveNets: Learning agnostic representations with application to face images

A Morales, J Fierrez, R Vera-Rodriguez… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
This work proposes a novel privacy-preserving neural network feature representation to
suppress the sensitive information of a learned space while maintaining the utility of the …

Personalized and invertible face de-identification by disentangled identity information manipulation

J Cao, B Liu, Y Wen, R **e… - Proceedings of the IEEE …, 2021 - openaccess.thecvf.com
The popularization of intelligent devices including smartphones and surveillance cameras
results in more serious privacy issues. De-identification is regarded as an effective tool for …

ADGAN: Protect your location privacy in camera data of auto-driving vehicles

Z **ong, Z Cai, Q Han, A Alrawais… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Computer vision and deep neural networks have been significantly promoting the
development of visual perception in these years. Particularly, for autonomous vehicles, real …

Privacy-preserving auto-driving: a GAN-based approach to protect vehicular camera data

Z **ong, W Li, Q Han, Z Cai - 2019 IEEE International …, 2019 - ieeexplore.ieee.org
The autonomous driving (auto-driving) technology has been promoted significantly by the
rapid advances in computer vision and deep neural networks. Auto-driving vehicles …