In-Context LoRA for Diffusion Transformers
Lianghua Huang Wei Wang Zhi-Fan Wu Yupeng Shi Huanzhang Dou Chen Liang Yutong Feng Yu Liu Jingren Zhou Tongyi Lab
Prompt: “This set of four images illustrates a young artist's creative process in a bright and inspiring studio; [IMAGE1] she stands before a large canvas, brush in hand, adding vibrant colors to a partially completed painting, [IMAGE2] she sits at a cluttered wooden table, sketching ideas in a notebook with various art supplies scattered around, [IMAGE3] she takes a moment to step back and observe her work, and [IMAGE4] she experiments with different textures by mixing paints directly on the palette, her focused expression showcasing her dedication to her craft.”
In-Context LoRA fine-tunes text-to-image models to generate image sets with customizable intrinsic relationships, optionally conditioned on another set, enabling adaptation to a wide range of tasks.
