Digital forensics is a topic that has attracted many attention. One of the most common tasks
in digital forensics is imaging sensor identification. It may be understood as recognizing …

Non-local self-similarity is well-known to be an effective prior for the image denoising
problem. However, little work has been done to incorporate it in convolutional neural …

State-of-the-art (SOTA) Generative Models (GMs) can synthesize photo-realistic images that
are hard for humans to distinguish from genuine photos. Identifying and understanding …

Sensors are an essential component of many computer systems today. Mobile devices are a
good example, containing a vast array of sensors from accelerometers and GPS units, to …

We address the problem of clustering a set of images, according to their source device, in
the absence of any prior information. Image similarity is computed based on noise residuals …

Photo response non-uniformity (PRNU) noise is a sensor pattern noise characterizing the
imaging device. It has been broadly used in the literature for source camera identification …

Millions of users share images and videos generated by mobile devices with different
profiles on social media platforms. When publishing illegal content, they prefer to use …

Recognizing information about the origin of a digital image has been individuated as a
crucial task to be tackled by the image forensic scientific community. Understanding …

A problem deeply investigated by multimedia forensics researchers is that of detecting which
device has been used to capture a video. This enables us to trace down the owner of a …

Source identification is an important topic in image forensics, since it allows to trace back the
origin of an image. This represents a precious information to claim intellectual property but …