MultiDiffusion enables versatile and controlled image generation through a unified framework that leverages pre-trained text-to-image diffusion models. The approach introduces a new generation process based on optimization to combine multiple diffusion paths, enabling versatile control over the generated image without any additional training or fine-tuning of the base model. The method supports various controlled generation tasks including regional editing, compositional generation, and style guidance by fusing multiple sampling trajectories.