We introduce Unimotion, the first unified multi-task human motion model capable of both flexible motion control and frame-level motion understanding. While existing works control avatar motion with global text conditioning, or with fine-grained per frame scripts, none can do both at once. In addition, none of the existing works can output frame-level text paired with the generated poses. In contrast, Unimotion allows to control motion with global text, or local frame-level text, or both at once, providing more flexible control for users. Importantly, Unimotion is the first model which by design outputs local text paired with the generated poses, allowing users to know what motion happens and when, which is necessary for a wide range of applications. We show Unimotion opens up new applications: 1.) Hierarchical control, allowing users to specify motion at different levels of detail, 2.) Obtaining motion text descriptions for existing MoCap data or YouTube videos 3.) Allowing for editability, generating motion from text, and editing the motion via text edits. Moreover, Unimotion attains state-of-the-art results for the frame-level text-to-motion task on the established HumanML3D dataset. The pre-trained model and code are available available on our project page at https://coral79.github.io/uni-motion/.

本研究提出了Unimotion，这是一种首个统一的多任务人类动作模型，能够同时进行灵活的动作控制和帧级动作理解。Unimotion允许通过全局文本、局部帧级文本或二者同时控制动作，为用户提供更大的灵活性，并首次实现了生成姿势时输出对应的局部文本，具有显著的应用潜力。

Unimotion：统一的3D人类动作合成与理解