Diffusion methods have been proven to be very effective to generate images while conditioning on a text prompt. However, and although the quality of the generated images is unprecedented, these methods seem to struggle when trying to generate specific image compositions. In this paper we present Mixture of Diffusers, an algorithm that builds over existing diffusion models to provide a more detailed control over composition. By harmonizing several diffusion processes acting on different regions of a canvas, it allows generating larger images, where the location of each object and style is controlled by a separate diffusion process.

翻译：扩散方法已被证明在基于文本提示生成图像方面非常有效。然而，尽管生成图像的质量达到了前所未有的水平，这些方法在尝试生成特定的图像构图时似乎仍面临挑战。本文提出混合扩散器算法，该算法基于现有扩散模型构建，以实现对构图的更精细控制。通过协调作用于画布不同区域的多个扩散过程，该方法能够生成更大尺寸的图像，其中每个对象和风格的位置由独立的扩散过程控制。