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 …

In this paper, we review recent work in media forensics for digital images, video, audio
(specifically speech), and documents. For each data modality, we discuss synthesis and …

Deepfakes are the result of digital manipulation to forge realistic yet fake imagery. With the
astonishing advances in deep generative models, fake images or videos are nowadays …

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

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

Multimedia data manipulation and forgery has never been easier than today, thanks to the
power of Artificial Intelligence (AI). AI-generated fake content, commonly called Deepfakes …

It is necessary to develop effective face forgery detection methods with constantly evolving
technologies in synthesizing realistic faces which raises serious risks on malicious face …

Various deepfake detectors have been proposed, but challenges still exist to detect images
of unknown categories or GAN models outside of the training settings. Such issues arise …

Due to its high societal impact, deepfake detection is getting active attention in the computer
vision community. Most deepfake detection methods rely on identity, facial attributes, and …

In the last few years, with the advancement of deep learning methods, especially Generative
Adversarial Networks (GANs) and Variational Auto-encoders (VAEs), fabricated content has …