# senguptaumd/Background-Matting

Background Matting: The World is Your Green Screen

Repository: https://github.com/senguptaumd/Background-Matting
Canonical: https://ross.abutalabs.com/products/background-matting
Homepage: https://grail.cs.washington.edu/projects/background-matting/
Language: Python
License Family: other
Last push: 2022-11-22T04:06:33+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2359, "days_push": 1380, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4769, forks 653 (observed 2026-08-28T04:08:59.341477+00:00)

## What it is
Official research code for 'Background Matting: The World is Your Green Screen' (CVPR 2020), a deep network that extracts per-pixel alpha mattes and foreground color of people from photos and videos using an extra background-only image instead of a green screen. It includes inference code for images and videos, training code on synthetic composites and unlabeled real videos, and a captured dataset.

## Use cases
- remove background from portrait photos without a green screen
- extract a person from video and composite onto a new background
- generate alpha mattes for video calls or virtual backgrounds
- train a matting model on synthetic composite data
- self-supervised matting training on unlabeled real videos

## When to choose
- you need research-grade background matting with an extra background frame available
- you want to reproduce CVPR 2020 matting results or build on the training code
- you need per-pixel alpha mattes rather than coarse segmentation masks

## When to avoid
- you need real-time 4K performance - use BackgroundMattingV2 instead
- you cannot capture a background-only image of the scene
- you need a permissively licensed production dependency - it is CC BY-NC-SA and unmaintained

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, image-processing, computer-vision
- domain: computer-vision, image-processing, deep-learning
- platform: python
- tags: background-matting, alpha-matting, green-screen, video-segmentation, research-code, cvpr-2020, linux, gpu

## Member repositories
- senguptaumd/Background-Matting (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:59.341477+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:18:49.191458+00:00, confidence not recorded.
  - readme: https://github.com/senguptaumd/Background-Matting (fetched 2026-08-28T04:08:59.341477+00:00, sha 75ea8a7787c9)
  - homepage: https://grail.cs.washington.edu/projects/background-matting/ (fetched 2026-08-29T09:02:10.919949+00:00, sha 355f3df2b65e)
- Data as of 2026-08-30T08:39:29.467469+00:00.