AnimateDiff is a modular motion-generation architecture that extends static text-to-image diffusion models with animation capabilities through a plug-and-play temporal Transformer module. The framework enables transformation of Stable Diffusion models into video generators without retraining the original image backbone, using a three-stage training pipeline involving domain adaptation, motion module learning, and optional MotionLoRA fine-tuning for specialized motion patterns.