Image Integrity

Image integrity research focuses on developing methods to detect and localize manipulations in digital images, ensuring authenticity and trustworthiness. Current approaches leverage diverse techniques, including deep learning architectures like transformers and generative adversarial networks (GANs), along with novel methods like embedding semantic information via watermarking and utilizing physical objects for verification. These advancements are crucial for various applications, from verifying scientific figures and satellite imagery to combating the spread of misinformation and enhancing the reliability of visual evidence in forensic investigations.