X-zhangyang/Real-World-Masked-Face-Dataset resource
Real-World Masked Face Dataset,口罩人脸数据集 observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 2393
- days_rel: n/a
- days_push: 651
- n_releases_24m: 0
Adoption not part of the score
2035 stars · 474 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A large-scale real-world dataset of masked and unmasked face images, collected and annotated by Wuhan University to support masked face detection, recognition, and verification research. It includes a 525-identity recognition set, simulated masked versions of standard benchmarks (WebFace, LFW, AgeDB-30, CFP-FP), and a verification set of 426 identities with matched/non-matched face pairs.
Use cases
- train a face recognition model that works when people wear masks
- find a labeled dataset of masked face images
- benchmark face verification accuracy under mask occlusion
- build a mask detection model for access control or gate systems
- evaluate face recognition on masked vs unmasked face pairs
- get simulated masked versions of standard face benchmarks like LFW
When to choose
- you need real-world photos of people wearing masks with identity labels for training or evaluation
- you want standardized verification pairs comparing masked and normal faces of the same identity
- you need masked variants of established benchmarks such as LFW, AgeDB-30, or CFP-FP
- you are researching occlusion-robust biometrics, e.g. for access control, attendance, or gate recognition
When to avoid
- you need a working algorithm or codebase rather than data - this repo is primarily a dataset with only demos
- you require a clear open-source license for commercial use - no license is specified in the repository
- you need general face datasets without masks, or very recent post-pandemic data
- your project depends on active software maintenance rather than a static data release
Facets
dataset · maturity stable
machine-learning computer-vision image-processing computer-vision machine-learning deep-learning image-processing artificial-intelligence python cross-platform masked-face-dataset face-recognition face-verification face-detection image-dataset covid-19 benchmark-dataset occluded-faces
1 source
- readme: https://github.com/X-zhangyang/Real-World-Masked-Face-Dataset · fetched 2026-08-28 · e38909a7ec9d
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| X-zhangyang/Real-World-Masked-Face-Dataset | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="X-zhangyang/Real-World-Masked-Face-Dataset")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem