CSGO: Content-Style Composition in Text-to-Image Generation

Understand

The diffusion model has shown exceptional capabilities in controlled image generation, which has further fueled interest in image style transfer.

• Existing works mainly focus on training free-based methods (e.g., image inversion) due to the scarcity of specific data.
• In this study, we present a data construction pipeline for content-style-stylized image triplets that generates and automatically cleanses stylized data triplets.
• Based on this pipeline, we construct a dataset IMAGStyle, the first large-scale style transfer dataset containing 210k image triplets, available for the community to explore and research.