With the rapid progress in recent years, techniques that generate and manipulate
multimedia content can now provide a very advanced level of realism. The boundary …

We are currently on a verge of a revolution in digital photography. Developments in
computational imaging and adoption of artificial intelligence have spawned new editing …

With the powerful deep network architectures, such as generative adversarial networks, one
can easily generate photorealistic images. Although the generated images are not …

The emergence of powerful image editing software has substantially facilitated digital image
tampering, leading to many security issues. Hence, it is urgent to identify tampered images …

Due to the wide diffusion of JPEG coding standard, the image forensic community has
devoted significant attention to the development of double JPEG (DJPEG) compression …

Accurate unsupervised tampering localization is one of the most challenging problems in
digital image forensics. In this paper, we consider a photo response non-uniformity analysis …

Editing a real-world photo through computer software or mobile applications is one of the
easiest things one can do today before sharing the doctored image on one's social …

Most existing image fusion methods assume that at least one input image contains high-
quality information at any place of an observed scene. Thus, these fusion methods will fail if …

Benefitting from the development of deep generative networks, modern fake news
generation methods called Deepfake rapidly go viral over the Internet, calling for efficient …

In this paper, we propose to utilize Convolutional Neural Networks (CNNs) and the
segmentation-based multi-scale analysis to locate tampered areas in digital images. First, to …