Extracting and Attributing Artistic Styles in Diffusion-based Image Generation Models

The core message of this article is to propose a framework for learning effective style descriptors from both labeled and unlabeled data, and then leveraging this model to investigate the extent of style copying in popular text-to-image generative models like Stable Diffusion.