GAN Fingerprint

GAN fingerprinting aims to identify the source of images generated by Generative Adversarial Networks (GANs), crucial for tracking misuse of these powerful models. Current research focuses on developing robust and retraining-free fingerprinting methods, often employing techniques like personalized normalization layers or representation mixing, and exploring how to detect these fingerprints even after image manipulation or attacks. This field is vital for combating the spread of deepfakes and ensuring responsible use of GANs in various applications, including copyright protection and combating misinformation.