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 …

Image is known as one of the communication tools between humans. With the development
and availability of digital devices such as cameras and cell phones, taking images has …

Recent advances in image editing techniques have posed serious challenges to the
trustworthiness of multimedia data, which drives the research of image tampering detection …

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 …

With advanced image journaling tools, one can easily alter the semantic meaning of an
image by exploiting certain manipulation techniques such as copy clone, object splicing …

We present a novel framework, Spatial Pyramid Attention Network (SPAN) for detection and
localization of multiple types of image manipulations. The proposed architecture efficiently …

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

We introduce a novel deep neural architecture for image copy-move forgery detection
(CMFD), code-named BusterNet. Unlike previous eorts, BusterNet is a pure, end-to-end …

Detecting and localizing image manipulation are necessary to counter malicious use of
image editing techniques. Accordingly, it is essential to distinguish between authentic and …