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MotionDiffuse: Text-Driven Human Motion Generation With Diffusion Model.

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    MotionDiffuse, a novel diffusion model, enables diverse and fine-grained human motion generation from text. This framework overcomes limitations in current text-driven motion synthesis, offering realistic and controllable results.

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    Area of Science:

    • Computer Graphics
    • Artificial Intelligence
    • Machine Learning

    Background:

    • Human motion modeling is crucial for graphics applications but requires specialized skills.
    • Existing text-driven motion generation methods struggle with diversity and fine-grained control.
    • Bridging the skill gap for laymen in motion generation is an ongoing challenge.

    Purpose of the Study:

    • To introduce MotionDiffuse, a diffusion model-based framework for text-driven human motion generation.
    • To enhance diversity, realism, and controllability in generating human motions from natural language.
    • To address the limitations of deterministic mapping in current motion generation techniques.

    Main Methods:

    • Developed MotionDiffuse, a framework utilizing a diffusion model for probabilistic text-motion mapping.
    • Employed a series of denoising steps to inject variations and generate diverse motions.
    • Implemented multi-level manipulation for fine-grained control over body parts and motion length.

    Main Results:

    • MotionDiffuse demonstrates superior performance over state-of-the-art methods in text-driven and action-conditioned motion generation.
    • The framework excels at modeling complex data distributions, leading to realistic and vivid motion sequences.
    • Qualitative analysis confirms MotionDiffuse's comprehensive controllability for motion generation tasks.

    Conclusions:

    • MotionDiffuse offers a significant advancement in text-driven human motion generation.
    • The probabilistic approach and multi-level manipulation capabilities provide enhanced realism and control.
    • This framework effectively lowers skill barriers for creating complex human motions using natural language.