emilianavt/OpenSeeFace

Health v2 · maintenance only

Adoption not part of the score

2038 stars · 205 forks observed · 2026-08-28

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

OpenSeeFace is a robust realtime face and facial landmark tracking library that runs on CPU at 30-60 fps using ONNX-converted MobileNetV3 models. It streams tracking data over UDP and includes Unity integration for animating avatars, powering tools like VSeeFace and VTube Studio.

Use cases

• track facial landmarks from a webcam in realtime on CPU
• animate a VRM avatar with webcam face tracking in Unity
• build a vtuber puppeteering app with head pose and expression tracking
• get stable face landmark detection in low light or noisy video
• stream face tracking data over UDP to another application
• compare face tracking robustness against MediaPipe

When to choose

• you need realtime face tracking on CPU without a GPU
• you want stable landmarks under poor lighting, noise, or extreme head poses
• you are building a vtuber or avatar animation tool with Unity or Godot integration
• you need a lightweight tracking library rather than a full end-user application

When to avoid

• you want a ready-made avatar puppeteering program - use VSeeFace or VTube Studio instead
• you need highly accurate eye-region tracking
• you require landmarks matching standard iBUG 68 conventions exactly
• you need GPU-accelerated multi-face tracking at scale

Facets

library · maturity active

computer-vision image-processing machine-learning sdk computer-vision machine-learning graphics developer-tools python windows cross-platform face-tracking facial-landmarks vtuber onnx unity udp realtime cpu-inference gpu

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markdown · JSON · MCP: product_card(name="emilianavt/OpenSeeFace")