pq-yang/MatAnyone

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

1625 stars · 114 forks observed · 2026-09-25

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

MatAnyone is a CVPR 2025 human video matting framework that extracts alpha mattes of target people from video using consistent memory propagation. It supports target assignment and provides inference code, a Gradio demo, Hugging Face integration, training code, and the YouTubeMatte evaluation benchmark.

Use cases

• remove or replace video backgrounds of people
• extract alpha mattes from video footage
• segment a specific person across video frames
• green-screen-free video compositing
• benchmark video matting models on YouTubeMatte
• run video matting in a browser demo

When to choose

• you need temporally stable human video matting with fine boundary details
• you want to mat a specific target person in multi-person scenes
• you need a research-grade model with training and evaluation code

When to avoid

• you need real-time matting on low-end hardware without a GPU
• you need general object matting rather than humans
• you want a maintained production successor - consider MatAnyone 2

Facets

library · maturity active

machine-learning image-processing video-processing computer-vision computer-vision deep-learning machine-learning python cross-platform video-matting alpha-matting background-removal segmentation cvpr-2025 gradio-demo huggingface video gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="pq-yang/MatAnyone")