Real Image

Real image research focuses on distinguishing authentic photographs from AI-generated images, a crucial task given the increasing realism and accessibility of generative models. Current research explores various detection methods, employing architectures like Swin Transformers, convolutional neural networks (CNNs), and normalizing flows, often leveraging frequency analysis, geometric properties, or subtle inconsistencies in generated images to achieve classification. This field is vital for combating misinformation, ensuring the authenticity of digital evidence, and improving the robustness of computer vision systems that rely on real-world image data.