2 citations · 3 across the 3 of their papers we have counts for
5 papers · 1 filter
Detecting GAN generated Fake Images using Co-occurrence Matrices
Lakshmanan Nataraj, Tajuddin Manhar Mohammed, Shivkumar Chandrasekaran +4
The advent of Generative Adversarial Networks (GANs) has brought about completely novel ways of transforming and manipulating pixels in digital images. GAN based techniques such as…
Deep Learning Methods for Event Verification and Image Repurposing Detection
M. Goebel, A. Flenner, L. Nataraj +1
The authenticity of images posted on social media is an issue of growing concern. Many algorithms have been developed to detect manipulated images, but few have investigated the ab…
Resampling Forgery Detection Using Deep Learning and A-Contrario Analysis
Arjuna Flenner, Lawrence Peterson, Jason Bunk +3
The amount of digital imagery recorded has recently grown exponentially, and with the advancement of software, such as Photoshop or Gimp, it has become easier to manipulate images.…
Boosting Image Forgery Detection using Resampling Features and Copy-move analysis
Tajuddin Manhar Mohammed, Jason Bunk, Lakshmanan Nataraj +6
Realistic image forgeries involve a combination of splicing, resampling, cloning, region removal and other methods. While resampling detection algorithms are effective in detecting…
Detection and Localization of Image Forgeries using Resampling Features and Deep Learning
Jason Bunk, Jawadul H. Bappy, Tajuddin Manhar Mohammed +6
Resampling is an important signature of manipulated images. In this paper, we propose two methods to detect and localize image manipulations based on a combination of resampling fe…