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 …

In recent decades, we have witnessed the evolution of information technologies from the
development of VLSI technologies, to communication and networking infrastructure, to the …

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 …

Forensic analyses of digital images rely heavily on the traces of in-camera and out-camera
processes left on the acquired images. Such traces represent a sort of camera fingerprint. If …

We propose a two-stream network for face tampering detection. We train GoogLeNet to
detect tampering artifacts in a face classification stream, and train a patch based triplet …

As manipulating images by copy-move, splicing and/or inpainting may lead to
misinterpretation of the visual content, detecting these sorts of manipulations is crucial for …

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 …

In this paper, we present a new image forgery detection method based on deep learning
technique, which utilizes a convolutional neural network (CNN) to automatically learn …

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 …

Distinguishing manipulated from real images is becoming increasingly difficult as new
sophisticated image forgery approaches come out by the day. Naive classification …