Inserting Anybody in Diffusion Models via Celeb Basis

Exquisite demand exists for customizing the pretrained large text-to-image model, e.g. Stable Diffusion, to generate innovative concepts, such as the users themselves. However, the newly-added concept from previous customization methods often shows weaker combination abilities than the original ones even given several images during training. We thus propose a new personalization method that allows for the seamless integration of a unique individual into the pre-trained diffusion model using just one\ facial\ photograph and only 1024\ learnable\ parameters under 3\ minutes . So we can effortlessly generate stunning images of this person in any pose or position, interacting with anyone and doing anything imaginable from text prompts.