Over the last few decades, rapid progress in AI, machine learning, and deep learning has
resulted in new techniques and various tools for manipulating multimedia. Though the …

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 this paper, we present novel synthetic training data called self-blended images (SBIs) to
detect deepfakes. SBIs are generated by blending pseudo source and target images from …

In this paper we propose a novel image representation called face X-ray for detecting
forgery in face images. The face X-ray of an input face image is a greyscale image that …

The recent proliferation of fake portrait videos poses direct threats on society, law, and
privacy [1]. Believing the fake video of a politician, distributing fake pornographic content of …

The rapid advancement of deep learning models that can generate and synthesis hyper-
realistic videos known as Deepfakes and their ease of access to the general public have …

Generative deep learning algorithms have progressed to a point where it is difficult to tell the
difference between what is real and what is fake. In 2018, it was discovered how easy it is to …

Deepfake refers to realistic, but fake images, sounds, and videos generated by articial
intelligence methods. Recent advances in deepfake generation make deepfake more …

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 …

When used maliciously, deepfake can pose detrimental implications to political and social
forces including reducing public trust in institutions, damaging the reputation of prominent …