87 citations · 168 across the 18 of their papers we have counts for
5 papers · 1 filter
Adversarial Robustness Comparison of Vision Transformer and MLP-Mixer to CNNs
Philipp Benz, Soomin Ham, Chaoning Zhang +2
Convolutional Neural Networks (CNNs) have become the de facto gold standard in computer vision applications in the past years. Recently, however, new model architectures have been…
Universal Adversarial Training with Class-Wise Perturbations
Philipp Benz, Chaoning Zhang, Adil Karjauv +1
Despite their overwhelming success on a wide range of applications, convolutional neural networks (CNNs) are widely recognized to be vulnerable to adversarial examples. This intrig…
A Brief Survey on Deep Learning Based Data Hiding
Chaoning Zhang, Chenguo Lin, Philipp Benz +3
Data hiding is the art of concealing messages with limited perceptual changes. Recently, deep learning has enriched it from various perspectives with significant progress. In this…
A Survey On Universal Adversarial Attack
Chaoning Zhang, Philipp Benz, Chenguo Lin +3
The intriguing phenomenon of adversarial examples has attracted significant attention in machine learning and what might be more surprising to the community is the existence of uni…
Universal Adversarial Perturbations Through the Lens of Deep Steganography: Towards A Fourier Perspective
Chaoning Zhang, Philipp Benz, Adil Karjauv +1
The booming interest in adversarial attacks stems from a misalignment between human vision and a deep neural network (DNN), i.e. a human imperceptible perturbation fools the DNN. M…