MagicAnimate

MagicAnimate is an open-source framework designed for human image animation, leveraging diffusion models to generate temporally consistent animated videos from a single static image and a motion video. The core functionality revolves around producing smooth, frame-by-frame animations that maintain the identity and appearance of the original reference image while faithfully following the motion patterns extracted from a driving video. Unlike many existing animation tools that suffer from flickering, distortion, or loss of detail over time, MagicAnimate specifically addresses temporal consistency by employing a diffusion-based architecture that aligns each generated frame with both the reference image and the preceding frames. This results in animations that appear fluid and natural, with minimal artifacts even over longer sequences. The framework accepts any human image—such as a photograph, a painting, or a stylized portrait—and a motion video that contains arbitrary human movements (e.g., dancing, walking, gesturing). The motion video does not need to match the person in the reference image; MagicAnimate can transfer the motion from one individual to another, enabling applications like converting a single portrait into a full-body dance video, creating character animations for games or films, or generating personalized avatars that mimic specific actions. The system processes the input by first extracting pose sequences from the motion video using a pose detector, then feeding these poses along with the reference image into a conditioned diffusion denoising U-Net. A temporal attention mechanism is integrated into the network to ensure that the generated frames remain coherent across time, avoiding common issues such as sudden identity shifts or background inconsistenci