7 citations · 10 across the 4 of their papers we have counts for
4 papers
Making Generated Images Hard To Spot: A Transferable Attack On Synthetic Image Detectors
Xinwei Zhao, Matthew C. Stamm
Visually realistic GAN-generated images have recently emerged as an important misinformation threat. Research has shown that these synthetic images contain forensic traces that are…
The Effect of Class Definitions on the Transferability of Adversarial Attacks Against Forensic CNNs
Xinwei Zhao, Matthew C. Stamm
In recent years, convolutional neural networks (CNNs) have been widely used by researchers to perform forensic tasks such as image tampering detection. At the same time, adversaria…
Defenses Against Multi-Sticker Physical Domain Attacks on Classifiers
Xinwei Zhao, Matthew C. Stamm
Recently, physical domain adversarial attacks have drawn significant attention from the machine learning community. One important attack proposed by Eykholt et al. can fool a class…
A Transferable Anti-Forensic Attack on Forensic CNNs Using A Generative Adversarial Network
Xinwei Zhao, Chen Chen, Matthew C. Stamm
With the development of deep learning, convolutional neural networks (CNNs) have become widely used in multimedia forensics for tasks such as detecting and identifying image forger…