MultiDiffusion: Fusing Diffusion Paths for Controlled Image Generation

Project page for 'MultiDiffusion: Fusing Diffusion Paths for Controlled Image Generation.'

Abstract Recent advances in text-to-image generation with diffusion models present transformative capabilities in image quality. However, user controllability of the generated image, and fast adaptation to new tasks still remains an open challenge, currently mostly addressed by costly and long re-training and fine-tuning or ad-hoc adaptations to specific image generation tasks. In this work, we present MultiDiffusion, a unified framework that enables versatile and controllable image generation, using a pre-trained text-to-image diffusion model, without any further training or finetuning. At…

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• Theo Ryzhenkov

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