With advancements in AI-generated images coming on a continuous basis, it is increasingly
difficult to distinguish traditionally-sourced images (eg, photos, artwork) from AI-generated …

The aim of this work is to explore the potential of pre-trained vision-language models (VLMs)
for universal detection of AI-generated images. We develop a lightweight detection strategy …

Recent advancements in deep generative models have facilitated the creation of photo-
realistic images across various tasks. However, these generated images often exhibit …

Recent generative models show impressive performance in generating photographic
images. Humans can hardly distinguish such incredibly realistic-looking AI-generated …

The heightened realism of AI-generated images can be attributed to the rapid development
of synthetic models, including generative adversarial networks (GANs) and diffusion models …

Text-to-image diffusion models (DM) have posed unprecedented challenges to the
authenticity and integrity of digital images, which makes the detection of computer …

New advancements for the detection of synthetic images are critical for fighting
disinformation, as the capabilities of generative AI models continuously evolve and can lead …

Distinguishing between computer-generated (CG) and natural photographic (PG) images is
of great importance to verify the authenticity and originality of digital images. However, the …

AI-based image generation has continued to rapidly improve producing increasingly more
realistic images with fewer obvious visual flaws. AI-generated images are being used to …

Recently, the proliferation of increasingly realistic synthetic images generated by various
generative adversarial networks has increased the risk of misuse. Consequently, there is a …