684 citations · 1.2k across the 33 of their papers we have counts for
5 papers · 1 filter
Exposing Deep Fakes Using Inconsistent Head Poses
Xin Yang, Yuezun Li, Siwei Lyu
In this paper, we propose a new method to expose AI-generated fake face images or videos (commonly known as the Deep Fakes). Our method is based on the observations that Deep Fakes…
Exposing DeepFake Videos By Detecting Face Warping Artifacts
Yuezun Li, Siwei Lyu
In this work, we describe a new deep learning based method that can effectively distinguish AI-generated fake videos (referred to as {\em DeepFake} videos hereafter) from real vide…
Exploring the Vulnerability of Single Shot Module in Object Detectors via Imperceptible Background Patches
Yuezun Li, Xiao Bian, Ming-ching Chang +1
Recent works succeeded to generate adversarial perturbations on the entire image or the object of interests to corrupt CNN based object detectors. In this paper, we focus on explor…
Robust Adversarial Perturbation on Deep Proposal-based Models
Yuezun Li, Daniel Tian, Ming-Ching Chang +2
Adversarial noises are useful tools to probe the weakness of deep learning based computer vision algorithms. In this paper, we describe a robust adversarial perturbation (R-AP) met…
In Ictu Oculi: Exposing AI Generated Fake Face Videos by Detecting Eye Blinking
Yuezun Li, Ming-Ching Chang, Siwei Lyu
The new developments in deep generative networks have significantly improve the quality and efficiency in generating realistically-looking fake face videos. In this work, we descri…