GuyTevet/motion-diffusion-model

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4092 stars · 458 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Official PyTorch implementation of the Human Motion Diffusion Model (MDM) paper, generating 3D human motion sequences from text prompts using diffusion models. Includes the faster DiP text-to-motion model and evaluation tooling on HumanML3D and KIT benchmarks.

Use cases

• generate human motion animations from text descriptions
• text-to-motion synthesis for character animation
• research baseline for motion diffusion models
• evaluate motion generation on HumanML3D benchmark
• create skeletal animation clips from prompts

When to choose

• you need a research-grade text-to-motion diffusion model in PyTorch
• you want to reproduce or extend the MDM paper
• you need fast motion generation with the DiP model

When to avoid

• you need production-ready animation tooling for game engines
• you want a GUI-based animation editor rather than a research codebase
• you work outside Python/PyTorch environments

Facets

library · maturity active

machine-learning deep-learning image-processing machine-learning deep-learning computer-vision python diffusion-model human-motion text-to-motion pytorch motion-generation research-code character-animation research gpu

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