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Generating art through large language models such as DALL-E has become popular, but one challenge is keeping a consistent style throughout a prompt when generating a series of images.
To address this, Google Research has developed StyleAligned, a method for achieving consistent style across images using a pre-trained diffusion model without the need for fine-tuning.
StyleAligned operates by encouraging information retention and style consistency through a shared attention mechanism, in which an image being generated attends to a user-provided reference image during the diffusion process.
The researchers demonstrate the efficacy of the method across a range of artistic styles and text prompts, showing that StyleAligned can produce a series of images that maintain a consistent visual style without the need for fine-tuning or manual intervention.
Styled aligned image generation can also be used in combination with other methods.