Recent years have seen a substantial increase in interest in deepfakes, a fast-develo**
field at the nexus of artificial intelligence and multimedia. These artificial media creations …

Differences in forgery attributes of images generated in CNN-synthesized and image-editing
domains are large, and such differences make a unified image forgery detection and …

The growing threats of deepfakes to society and cybersecurity have raised enormous public
concerns, and increasing efforts have been devoted to this critical topic of deepfake video …

In recent years, as various realistic face forgery techniques known as DeepFake improves
by leaps and bounds, more and more DeepFake detection techniques have been proposed …

The creation or manipulation of facial appearance through deep generative approaches,
known as DeepFake, have achieved significant progress and promoted a wide range of …

As the GAN-based face image and video generation techniques, widely known as
DeepFakes, have become more and more matured and realistic, there comes a pressing …

In recent years, generative adversarial networks (GANs) and its variants have achieved
unprecedented success in image synthesis. They are widely adopted in synthesizing facial …

With the large chunks of social media data being created daily and the parallel rise of
realistic multimedia tampering methods, detecting and localising tampering in images and …

Abstract DeepFake uses Generative+ Adversarial Network for successfully switching the
identities of two people. Large public databases and deep learning methods are now rapidly …

With the increasing availability of sophisticated deep learning techniques, the production of
manipulated images, videos, and audios, commonly known as deep-fakes, has become …