Recently, deepfake videos, generated by deep learning algorithms, have attracted
widespread attention. Deepfake technology can be used to perform face manipulation with …

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 …

We present our on-going effort of constructing a large-scale benchmark for face forgery
detection. The first version of this benchmark, DeeperForensics-1.0, represents the largest …

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 …

With recent advances in computer vision and graphics, it is now possible to generate videos
with extremely realistic synthetic faces, even in real time. Countless applications are …

The rapid progress in synthetic image generation and manipulation has now come to a point
where it raises significant concerns for the implications towards society. At best, this leads to …

In 2018, clinics and hospitals were hit with numerous attacks leading to significant data
breaches and interruptions in medical services. An attacker with access to medical records …

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

In the last years, due to the availability and easy of use of image editing tools, a large
amount of fake and altered images have been produced and spread through the media and …

This paper proposes a splicing forgery detection method with two parts: a coarse-to-refined
convolutional neural network (C2RNet) and diluted adaptive clustering. The proposed …