nv-tlabs/kimodo

Health v2 · maintenance only

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3615 stars · 399 forks observed · 2026-09-23

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

Kimodo is NVIDIA's official implementation of a kinematic motion diffusion model trained on 700 hours of motion capture data to generate high-quality 3D human and robot motions. It supports text-prompt control plus kinematic constraints (pose keyframes, end-effector targets, 2D paths), and ships with a CLI, an interactive timeline demo, and a motion generation benchmark.

Use cases

• generate 3D human motion animations from text prompts
• create humanoid robot motions controlled by end-effector constraints
• author character animations with a timeline of prompts and keyframe poses
• benchmark and evaluate motion generation models on text and constraint following
• generate motion sequences from 2D paths and waypoints
• produce training or simulation data for humanoid robotics

When to choose

• you need high-quality text- or constraint-controlled 3D human or humanoid motion generation
• you want an interactive tool to author motions with prompts and kinematic controls
• you need a standardized benchmark for comparing motion generation models
• you work with human or robot skeletons like SOMA, G1, or SMPL-X

When to avoid

• you need real-time motion generation rather than offline diffusion inference
• you lack a GPU or work with very limited VRAM
• you need physics-based or physically simulated motion rather than kinematic motion
• you need a lightweight production animation tool without ML dependencies

Facets

library · maturity active

machine-learning deep-learning llm-inference cli benchmarking data-generation machine-learning deep-learning artificial-intelligence robotics simulation gaming-tools python cli motion-diffusion motion-generation human-motion text-to-motion motion-capture humanoid diffusion-model animation nvidia linux gpu

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markdown · JSON · MCP: product_card(name="nv-tlabs/kimodo")