Diffusion Generated Image

Diffusion-generated images leverage diffusion models to create realistic synthetic images, primarily aiming to improve data augmentation for various applications and to detect such generated images. Current research focuses on enhancing controllability and quality of generation, developing robust detection methods (often using reconstruction error or feature analysis), and applying these techniques to specific domains like medical imaging and video. This field is significant due to its potential to address data scarcity issues in machine learning, improve the realism of synthetic data for training, and mitigate the risks associated with deepfakes and other forms of AI-generated misinformation.