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:传播方法已证明非常有效,既能生成图像,又能同时以文本提示为条件。 然而,尽管生成图像的质量是前所未有的,但这些方法在试图生成特定图像构造时似乎很难做到。 在本文件中,我们展示了Diffusers的混集法,这种混集法建立在现有的扩散模型之上,以提供对构成的更详细控制。通过在画布的不同区域协调若干扩散过程,它能够生成更大的图像,其中每个对象和风格的位置都由单独的传播过程控制。