X-LANCE/AniTalker

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1598 stars · 144 forks observed · 2026-08-28

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

AniTalker is the official PyTorch implementation of an ACM MM 2024 paper that animates a single static portrait into a vivid talking-face video driven by input audio. It uses identity-decoupled facial motion encoding with self-supervised learning and a diffusion model with a variance adapter to produce diverse, realistic facial expressions and head movements.

Use cases

• generate a talking head video from a single portrait and audio clip
• animate an avatar's face with lip sync and nonverbal expressions
• create diverse talking face animations from the same control signals
• build dynamic digital avatars for virtual presenters
• research identity-decoupled facial motion representation
• run a web UI or Colab demo for audio-driven face animation

When to choose

• you need audio-driven talking face generation from a single image
• you want diverse, nonverbal facial motion rather than only lip sync
• you are reproducing or extending the AniTalker research
• you want a ready web UI, Colab, or Hugging Face demo to try the model

When to avoid

• you need real-time or production-grade streaming avatar generation
• you lack a GPU or cannot download external checkpoints
• you need fine-grained manual control over facial rigging like 3D puppet tools
• you need a maintained product with long-term support rather than research code

Facets

library · maturity active

machine-learning deep-learning image-processing audio-processing video-processing artificial-intelligence computer-vision deep-learning media python windows talking-face talking-head face-animation audio-driven diffusion-model avatar-generation lip-sync research-code acm-mm-2024 linux macos gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="X-LANCE/AniTalker")