In current years, the improvement of deep learning has brought about tremendous changes:
As a type of unsupervised deep learning algorithm, generative adversarial networks (GANs) …

Although effective deepfake detection models have been developed in recent years recent
studies have revealed that these models can result in unfair performance disparities among …

Generative adversarial network (GAN) generated high-realistic human faces are visually
challenging to discern from real ones. They have been used as profile images for fake social …

Despite the development of effective deepfake detectors in recent years, recent studies have
demonstrated that biases in the data used to train these detectors can lead to disparities in …

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 …

Denoising Diffusion Models (DDMs) have emerged as a strong competitor to Generative
Adversarial Networks (GANs). However, despite their widespread use in image synthesis …

Recent advancements in language-image models have led to the development of highly
realistic images that can be generated from textual descriptions. However, the increased …

With the development of the Generative Adversarial Networks (GANs) and DeepFakes, AI-
synthesized images are now of such high quality that humans can hardly distinguish them …

With the rapid development of deep generative models (such as Generative Adversarial
Networks and Diffusion models), AI-synthesized images are now of such high quality that …

Disinformation can be used to sway public opinion toward a certain political or economic
direction, adversely impact public health, and mobilize groups to engage in violent …