88 citations · 199 across the 18 of their papers we have counts for
5 papers · 1 filter
Unrestricted Adversarial Attacks on ImageNet Competition
Yuefeng Chen, Xiaofeng Mao, Yuan He +34
Many works have investigated the adversarial attacks or defenses under the settings where a bounded and imperceptible perturbation can be added to the input. However in the real-wo…
Restoration of Video Frames from a Single Blurred Image with Motion Understanding
Dawit Mureja Argaw, Junsik Kim, Francois Rameau +2
We propose a novel framework to generate clean video frames from a single motion-blurred image. While a broad range of literature focuses on recovering a single image from a blurre…
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…
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…
Self-Adaptive Training: Bridging Supervised and Self-Supervised Learning
Lang Huang, Chao Zhang, Hongyang Zhang
We propose self-adaptive training -- a unified training algorithm that dynamically calibrates and enhances training processes by model predictions without incurring an extra comput…