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 …

Seeing is not believing anymore. Different techniques have brought to our fingertips the
ability to modify an image. As the difficulty of using such techniques decreases, lowering the …

To defend against manipulation of image content, such as splicing, copy-move, and
removal, we develop a Progressive Spatio-Channel Correlation Network (PSCC-Net) to …

To fight against real-life image forgery, which commonly involves different types and
combined manipulations, we propose a unified deep neural architecture called ManTra-Net …

Advances in photo editing and manipulation tools have made it significantly easier to create
fake imagery, highlighting the need for better visual forensics algorithms. However, learning …

Digital image authenticity has promoted research on image forgery localization. Although
deep learning-based methods achieve remarkable progress, most of them usually suffer …

The increasing abuse of image editing softwares, such as Photoshop and Meitu, causes the
authenticity of digital images questionable. Meanwhile, the widespread availability of online …

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 …

Deep learning (DL) has demonstrated its powerful capabilities in the field of image
inpainting, which could produce visually plausible results. Meanwhile, the malicious use of …

With the recent advancement in modern technology, one can easily manipulate a digital
image or video using computer software or a mobile application. The purpose of editing …