facebookresearch/audio2photoreal resource

Health v2 · maintenance only

Flags: archived no_license

Adoption not part of the score

2850 stars · 282 forks observed · 2026-08-28

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

A PyTorch codebase and dataset from Meta Research for generating photorealistic conversational avatars (face and body motion) driven from audio. It includes training and inference code, pretrained diffusion and VQ-VAE models, and a Gradio demo for rendering avatars from recorded audio.

Use cases

• generate a photorealistic avatar video from an audio clip
• train audio-driven body and face motion models
• research conversational avatar gesture synthesis
• visualize human conversation motion capture data
• run a demo that renders talking humans from microphone input
• reproduce CVPR paper results on audio-to-embodiment synthesis

When to choose

• you need research-grade audio-driven avatar motion generation with pretrained models
• you want the accompanying conversational gesture dataset for training
• you want to extend or reproduce state-of-the-art photorealistic avatar research

When to avoid

• you need a production-ready avatar SDK or end-user product
• you lack a CUDA GPU or the rendering pipeline dependencies
• you need real-time low-latency avatar animation in a commercial app
• you want simple text-to-avatar generation without audio

Facets

dataset · maturity active

machine-learning deep-learning audio-processing computer-vision graphics simulation machine-learning computer-vision graphics artificial-intelligence python codec-avatars audio-driven-animation diffusion-models human-motion conversational-agents pytorch research-code face-and-body-generation gpu linux

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markdown · JSON · MCP: product_card(name="facebookresearch/audio2photoreal")