Synthetic Image Detection

Synthetic image detection aims to distinguish computer-generated images from real photographs, a crucial task given the increasing realism and proliferation of AI-generated content. Current research focuses on developing detectors robust to diverse image generation models (GANs, diffusion models, etc.) and various image manipulations, often employing techniques like contrastive learning, vision-language models (VLMs), and ensemble methods to improve generalization and accuracy. This field is vital for combating misinformation, protecting online security, and ensuring the integrity of digital media, with ongoing efforts to create more comprehensive benchmark datasets and evaluation frameworks to better assess detector performance in real-world scenarios.