591 citations · 1.2k across the 45 of their papers we have counts for
11 papers · 1 filter
DeepRepair: Style-Guided Repairing for DNNs in the Real-world Operational Environment
Bing Yu, Hua Qi, Qing Guo +4
Deep neural networks (DNNs) are being widely applied for various real-world applications across domains due to their high performance (e.g., high accuracy on image classification).…
EfficientDeRain: Learning Pixel-wise Dilation Filtering for High-Efficiency Single-Image Deraining
Qing Guo, Jingyang Sun, Felix Juefei-Xu +4
Single-image deraining is rather challenging due to the unknown rain model. Existing methods often make specific assumptions of the rain model, which can hardly cover many diverse…
Adversarial Rain Attack and Defensive Deraining for DNN Perception
Liming Zhai, Felix Juefei-Xu, Qing Guo +5
Rain often poses inevitable threats to deep neural network (DNN) based perception systems, and a comprehensive investigation of the potential risks of the rain to DNNs is of great…
Generating Adversarial Examples with Controllable Non-transferability
Renzhi Wang, Tianwei Zhang, Xiaofei Xie +4
Adversarial attacks against Deep Neural Networks have been widely studied. One significant feature that makes such attacks particularly powerful is transferability, where the adver…
DeepRhythm: Exposing DeepFakes with Attentional Visual Heartbeat Rhythms
Hua Qi, Qing Guo, Felix Juefei-Xu +5
As the GAN-based face image and video generation techniques, widely known as DeepFakes, have become more and more matured and realistic, there comes a pressing and urgent demand fo…
FakePolisher: Making DeepFakes More Detection-Evasive by Shallow Reconstruction
Yihao Huang, Felix Juefei-Xu, Run Wang +7
At this moment, GAN-based image generation methods are still imperfect, whose upsampling design has limitations in leaving some certain artifact patterns in the synthesized image.…
Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning
Jianwen Sun, Tianwei Zhang, Xiaofei Xie +4
Adversarial attacks against conventional Deep Learning (DL) systems and algorithms have been widely studied, and various defenses were proposed. However, the possibility and feasib…
DeepSonar: Towards Effective and Robust Detection of AI-Synthesized Fake Voices
Run Wang, Felix Juefei-Xu, Yihao Huang +4
With the recent advances in voice synthesis, AI-synthesized fake voices are indistinguishable to human ears and widely are applied to produce realistic and natural DeepFakes, exhib…
Byzantine-resilient Decentralized Stochastic Gradient Descent
Shangwei Guo, Tianwei Zhang, Han Yu +4
Decentralized learning has gained great popularity to improve learning efficiency and preserve data privacy. Each computing node makes equal contribution to collaboratively learn a…
Watch out! Motion is Blurring the Vision of Your Deep Neural Networks
Qing Guo, Felix Juefei-Xu, Xiaofei Xie +5
The state-of-the-art deep neural networks (DNNs) are vulnerable against adversarial examples with additive random-like noise perturbations. While such examples are hardly found in…
FakeLocator: Robust Localization of GAN-Based Face Manipulations
Yihao Huang, Felix Juefei-Xu, Qing Guo +2
Full face synthesis and partial face manipulation by virtue of the generative adversarial networks (GANs) and its variants have raised wide public concerns. In the multi-media fore…