We propose MikuDance, a diffusion-based pipeline incorporating mixed motion dynamics to animate stylized character art. MikuDance consists of two key techniques: Mixed Motion Modeling and Mixed-Control Diffusion, to address the challenges of high-dynamic motion and reference-guidance misalignment in character art animation. Specifically, a Scene Motion Tracking strategy is presented to explicitly model the dynamic camera in pixel-wise space, enabling unified character-scene motion modeling. Building on this, the Mixed-Control Diffusion implicitly aligns the scale and body shape of diverse characters with motion guidance, allowing flexible control of local character motion. Subsequently, a Motion-Adaptive Normalization module is incorporated to effectively inject global scene motion, paving the way for comprehensive character art animation. Through extensive experiments, we demonstrate the effectiveness and generalizability of MikuDance across various character art and motion guidance, consistently producing high-quality animations with remarkable motion dynamics.

翻译：我们提出了MikuDance，一种融合混合运动动力学的基于扩散模型的流程，用于驱动风格化角色艺术动画。MikuDance包含两项关键技术：混合运动建模与混合控制扩散，以应对角色艺术动画中高动态运动和参考引导错位的挑战。具体而言，我们提出了一种场景运动跟踪策略，在像素级空间中显式建模动态摄像机，从而实现角色与场景运动的统一建模。在此基础上，混合控制扩散隐式地将多样化角色的尺度和体型与运动引导对齐，允许对角色局部运动进行灵活控制。随后，我们引入了一个运动自适应归一化模块，以有效注入全局场景运动，为全面的角色艺术动画铺平道路。通过大量实验，我们证明了MikuDance在多种角色艺术和运动引导下的有效性和泛化能力，能够持续生成具有卓越运动动力学的高质量动画。