AnimateDiff offers a framework for animating text-to-image models like Stable Diffusion, DreamBooth, and LoRA. This framework upgrades the animation process by incorporating a motion modeling module, efficiently trained on video clips, eliminating the need for intricate model-specific tuning.

At its core, AnimateDiff introduces a motion modeling module into the text-to-image model, trained on video clips to distill coherent motion priors. This approach provides universality, enabling the animation of various personalized text-to-image models derived from the same base, saving considerable efforts in model-specific adjustments.