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 …

In this paper we present TruFor, a forensic framework that can be applied to a large variety
of image manipulation methods, from classic cheapfakes to more recent manipulations …

In the era of AI-generated content (AIGC) malicious tampering poses imminent threats to
copyright integrity and information security. Current deep image watermarking while widely …

The introduction of publicly available large-scale datasets and advances in generative
adversarial networks (GANs) have revolutionized the generation of hyper-realistic facial …

Recently, the spread of fake images on social media platforms has become a significant
concern for individuals, organizations, and governments. These images are often created …

Recently, tampered text detection in document image has attracted increasingly attention
due to its essential role on information security. However, detecting visually consistent …

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 …

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 …

RAW files are the initial measurement of scene radiance widely used in most cameras, and
the ubiquitously-used RGB images are converted from RAW data through Image Signal …

Modern image editing software enables anyone to alter the content of an image to deceive
the public, which can pose a security hazard to personal privacy and public safety. The …