52 citations · 205 across the 20 of their papers we have counts for
6 papers · 2 filters
Can You Spot the Chameleon? Adversarially Camouflaging Images from Co-Salient Object Detection
Ruijun Gao, Qing Guo, Felix Juefei-Xu +5
Co-salient object detection (CoSOD) has recently achieved significant progress and played a key role in retrieval-related tasks. However, it inevitably poses an entirely new safety…
Dodging DeepFake Detection via Implicit Spatial-Domain Notch Filtering
Yihao Huang, Felix Juefei-Xu, Qing Guo +2
The current high-fidelity generation and high-precision detection of DeepFake images are at an arms race. We believe that producing DeepFakes that are highly realistic and 'detecti…
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…
Pasadena: Perceptually Aware and Stealthy Adversarial Denoise Attack
Yupeng Cheng, Qing Guo, Felix Juefei-Xu +4
Image denoising can remove natural noise that widely exists in images captured by multimedia devices due to low-quality imaging sensors, unstable image transmission processes, or l…
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.…