Multimodal · Efficiency

MotionGPT

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Paper summary

Generates consecutive human motions from multimodal control signals via LLM instructions.

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Key points

Motion quantization: Quantizes motion into discrete tokens that LLMs can produce in the same stream as text.

Multimodal control: Accepts text, audio, and other control signals as input, producing corresponding human motion outputs.

LLM-as-motion-generator: Treats motion generation as a token-prediction task, unifying motion with other LLM capabilities.

Animation and VR: Applicable to character animation, VR avatars, and content creation workflows where text-driven motion is valuable.

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