MikuDance - a hybrid animation generation technology that transforms static images into dynamically stylized character art.

What is MikuDance?

MikuDance is an animation generation technology based on a diffusion model that integrates hybrid motion dynamics to animate stylized character art. Based on hybrid motion modeling and hybrid control diffusion techniques, MikuDance solves problems related to high-dynamic motion and reference guidance misalignment. It can explicitly model dynamic camera and character motion, and implicitly align character shape, pose, and proportions to achieve coherent motion control. MikuDance demonstrates effectiveness and generalization capabilities across various character art styles and motion guides, generating high-quality animations with significant motion dynamics.

MikuDance's main functions

• Animated stylized character artMikuDance can transform static character images into dynamic animations, making it suitable for stylized character art, such as anime-style characters.
• Handling high dynamic motionIt can handle high dynamic range motion in complex foregrounds and backgrounds, including large character movements and rapid camera movements.
• Reference Guided AlignmentBased on implicit alignment technology, it addresses the misalignment between character shape, pose, and proportion and motion guidance.
• Global and local motion controlIt combines scene motion tracking and motion adaptive normalization modules to control both global scene motion and local character motion.
• Multi-style adaptabilityMikuDance adapts to a variety of art styles, including cel, classical, and line drawing, demonstrating strong versatility.

MikuDance's technical principles

• Hybrid motion modelingMikuDance converts 3D camera poses into pixel-level scene motion representations, explicitly modeling dynamic camera and character motion to achieve unified motion modeling of characters and scenes.
• Hybrid Controlled DiffusionThis integrates reference character art, reference poses, and all character pose guides into a unified potential space, enabling aligned motion control of the animation.
• Motion Adaptive Normalization ModuleIt effectively injects global scene motion into character animation, supporting comprehensive character model animation generation.
• Hybrid Source Training MethodA two-stage training method is adopted. In the first stage, paired video frames are used for training. In the second stage, a MAN module and a temporal module are added, and the model is trained with mixed MMD video clips and camera motion videos without characters to enhance the robustness and generalization ability of the model.
• Prerequisites for Stable DiffusionMikuDance is based on the Stable Diffusion (SD) model, which includes a VAE for automatic image encoding and a UNet for noise estimation. It transforms noisy images into latent images step by step based on a backdiffusion process.

MikuDance's project address

• Project official website:kebii.github.io/MikuDance
• GitHub repository:https://github.com/Kebii/MikuDance(Coming soon to be open source)
• arXiv technical paper:https://arxiv.org/pdf/2411.08656

Application scenarios of MikuDance

• Game developmentIn game development, it can quickly generate character animations, reducing the cost and time of traditional animation production.
• Film and television productionIn the post-production of movies and TV series, it creates complex dynamic scenes and special effects to enhance visual impact.
• Virtual Reality (VR) and Augmented Reality (AR)In VR and AR applications, dynamic characters that interact with users are generated to enhance immersion.
• Animation ProductionIt provides a new way of generating animation for traditional 2D or 3D animation, especially for stylized character animation.
• Social media content creationContent creators generate engaging animated images and videos for use on social media platforms.