3 citations · 3 across the 4 of their papers we have counts for
5 papers
Occlusion-Robust FAU Recognition by Mining Latent Space of Masked Autoencoders
Minyang Jiang, Yongwei Wang, Martin J. McKeown +1
Facial action units (FAUs) are critical for fine-grained facial expression analysis. Although FAU detection has been actively studied using ideally high quality images, it was not…
Delving into Deep Image Prior for Adversarial Defense: A Novel Reconstruction-based Defense Framework
Li Ding, Yongwei Wang, Xin Ding +4
Deep learning based image classification models are shown vulnerable to adversarial attacks by injecting deliberately crafted noises to clean images. To defend against adversarial…
Perception Improvement for Free: Exploring Imperceptible Black-box Adversarial Attacks on Image Classification
Yongwei Wang, Mingquan Feng, Rabab Ward +2
Deep neural networks are vulnerable to adversarial attacks. White-box adversarial attacks can fool neural networks with small adversarial perturbations, especially for large size i…
Perception Matters: Exploring Imperceptible and Transferable Anti-forensics for GAN-generated Fake Face Imagery Detection
Yongwei Wang, Xin Ding, Li Ding +2
Recently, generative adversarial networks (GANs) can generate photo-realistic fake facial images which are perceptually indistinguishable from real face photos, promoting research…
A Deep Learning Based Attack for The Chaos-based Image Encryption
Chen He, Kan Ming, Yongwei Wang +1
In this letter, as a proof of concept, we propose a deep learning-based approach to attack the chaos-based image encryption algorithm in \cite{guan2005chaos}. The proposed method f…