What is MikuDance
MikuDance is a diffusion model-based animation generation technology that integrates hybrid motion dynamics to animate stylized character art. Based on hybrid motion modeling and hybrid control diffusion technology, MikuDance addresses high-dynamic motion and reference-guided misalignment issues. It can explicitly model dynamic camera and character motion, and implicitly align character shape, pose, and proportions, achieving coherent motion control. MikuDance demonstrates effectiveness and generalization ability under various character art and motion guidance, generating high-quality animations with significant motion dynamics.
Main Features of MikuDance
- Animating Stylized Character Art: MikuDance can transform static character images into dynamic animations, suitable for stylized character art such as anime style.
- Handling High-Dynamic Motion: It can handle complex high-dynamic motion in the foreground and background, including large-scale character movements and rapid camera movements.
- Reference-Guided Alignment: Based on implicit alignment technology, it addresses the misalignment issues between character shape, pose, and proportions and motion guidance.
- Global and Local Motion Control: Combining scene motion tracking and motion-adaptive normalization modules, it simultaneously controls global scene motion and local character motion.
- Multi-Style Adaptability: MikuDance adapts to various art styles, including cel-shading, classical style, and line sketches, demonstrating strong generalization ability.
Technical Principles of MikuDance
- Hybrid Motion Modeling: By converting 3D camera poses into pixel-level scene motion representations, MikuDance explicitly models dynamic camera and character motion, achieving unified motion modeling of characters and scenes.
- Hybrid Control Diffusion: It integrates reference character art, reference poses, and all character pose guidance into a unified latent space, achieving aligned motion control for animation.
- Motion-Adaptive Normalization Module: It effectively injects global scene motion into character animation, supporting comprehensive character styling animation generation.
- Hybrid Source Training Method: It adopts a two-stage training method. The first stage uses paired video frames for training, and the second stage adds the MAN module and temporal module, using mixed MMD video clips and camera motion videos without characters for training, enhancing the model's robustness and generalization ability.
- Preliminary Knowledge of Stable Diffusion: MikuDance is based on the Stable Diffusion (SD) model. The model includes a VAE for autoencoding images and a UNet for noise estimation, gradually transforming noisy images into latent images based on the reverse diffusion process.
Project Address of MikuDance
- Project Website：kebii.github.io/MikuDance
- GitHub Repository：https://github.com/Kebii/MikuDance(to be open-sourced)
- arXiv Technical Paper：https://arxiv.org/pdf/2411.08656
Application Scenarios of MikuDance
- Game Development: In game production, it quickly generates character animations, reducing the cost and time of traditional animation production.
- Film and Television Production: In post-production of films and TV series, it creates complex dynamic scenes and special effects, enhancing visual impact.
- Virtual Reality (VR) and Augmented Reality (AR): In VR and AR applications, it generates dynamic characters that interact with users, enhancing immersion.
- Animation Production: For traditional 2D or 3D animation, provide a new animation generation method, especially for stylized character animation.
- Social media content creation: Content creators generate attractive dynamic images and videos for use on social media platforms.