By mining community LoRAs as style-content anchors and using curriculum learning with targeted disentanglement mechanisms, you can scale dual-reference image generation while maintaining clean separation between style and content.
FreeStyle is a framework for generating images that combine the style of one image with the content of another. It uses community LoRA models as building blocks to create large training datasets and employs specialized techniques to prevent unwanted style or content leakage. The approach includes a new benchmark for evaluating dual-reference image generation.