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Story-to-Motion: Synthesizing Infinite and Controllable Character Animation from Long Text

Zhongfei Qing     Zhongang Cai     Zhitao Yang     Lei Yang✉
SenseTime Research
✉Corresponding Author
Paper arXiv Video
teaser

Story-to-Motion is a new task that takes a story (top green area) and generates motions and trajectories that align with the text description.

Abstract

Generating natural human motion from a story has the potential to transform the landscape of animation, gaming, and film industries. A new and challenging task, Story-to-Motion, arises when characters are required to move to various locations and perform specific motions based on a long text description. This task demands a fusion of low-level control (trajectories) and high-level control (motion semantics). Previous works in character control and text-to-motion have addressed related aspects, yet a comprehensive solution remains elusive: character control methods do not handle text description, whereas text-to-motion methods lack position constraints and often produce unstable motions. In light of these limitations, we propose a novel system that generates controllable, infinitely long motions and trajectories aligned with the input text. 1) we leverage contemporary Large Language Models to act as a text-driven motion scheduler to extract a series of (text, position) pairs from long text. 2) we develop a text-driven motion retrieval scheme that incorporates classic motion matching with motion semantic and trajectory constraints. 3) we design a progressive mask transformer that addresses common artifacts in the transition motion such as unnatural pose and foot sliding. Beyond its pioneering role as the first comprehensive solution for Story-to-Motion, our system undergoes evaluation across three distinct sub-tasks: trajectory following, temporal action composition, and motion blending, where it outperforms previous state-of-the-art (SOTA) motion synthesis methods across the board.

Video

BibTeX

@misc{qing2023storytomotion,
        title={Story-to-Motion: Synthesizing Infinite and Controllable Character Animation from Long Text}, 
        author={Zhongfei Qing and Zhongang Cai and Zhitao Yang and Lei Yang},
        year={2023},
        eprint={2311.07446},
        archivePrefix={arXiv},
        primaryClass={cs.CV}
  }