CyberAgentAILab/TANGO

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1163 stars · 149 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

TANGO is a research library from CyberAgent AI Lab that generates co-speech gesture videos by reenactment, using hierarchical audio-motion embeddings (AuMoClip) and diffusion interpolation. It was published as an ICLR 2025 Oral paper and includes inference and training code with pretrained weights.

Use cases

• generate talking gesture videos from speech audio
• reenact a reference speaker video with new speech
• synthesize realistic body gestures synced to audio
• research on audio-driven human motion generation
• create virtual presenter videos from a script
• train audio-to-motion diffusion models

When to choose

• you need audio-driven gesture video generation with pretrained weights
• you want to reproduce or extend an ICLR 2025 research result
• you have a GPU environment and Python 3.10/CUDA 11.8 available
• you want a Hugging Face demo-backed gesture synthesis pipeline

When to avoid

• you need production-grade, licensed software (license is non-standard)
• you lack a CUDA GPU or cannot handle heavy model dependencies
• you need real-time or low-latency generation (inference takes minutes per clip)
• you want a polished end-user application rather than research code

Facets

library · maturity active

deep-learning video-processing audio-processing machine-learning llm-inference deep-learning computer-vision artificial-intelligence python co-speech-gesture video-reenactment diffusion-models audio-motion-embedding talking-head iclr-2025 gesture-generation research-code audio video linux gpu docker

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For agents

markdown · JSON · MCP: product_card(name="CyberAgentAILab/TANGO")