verlab/accelerated_features
Implementation of XFeat (CVPR 2024). Do you need robust and fast local feature extraction? You are in the right place! observed · 2026-08-28
Health v2 · maintenance only
16/100
- Activity 1
- Release rhythm 8
- Longevity 62
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: 870
- days_rel: n/a
- days_push: 595
- n_releases_24m: 0
Adoption not part of the score
1716 stars · 233 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
XFeat is a lightweight, fast learned keypoint detector and descriptor for local feature extraction and image matching, supporting both sparse and semi-dense matching. It runs in real-time on CPUs without specialized hardware, making it suitable for resource-limited devices.
Use cases
- extract keypoints and descriptors from images
- match features between two images in real time
- register images on CPU without GPU
- build visual odometry or SLAM frontends
- augmented reality tracking on resource-limited devices
- visual localization and pose estimation
- replace SIFT with a faster learned alternative
When to choose
- you need fast, robust local feature matching on CPU or edge devices
- you want sparse or semi-dense matching with a single lightweight model
- you need real-time performance for AR, navigation, or robotics
When to avoid
- you need state-of-the-art accuracy regardless of compute cost
- your pipeline depends on a different feature ecosystem like SuperPoint+SuperGlue with heavy GPU matching
Facets
library · maturity active
computer-vision image-processing machine-learning computer-vision image-processing robotics python cross-platform keypoint-detection image-matching image-registration local-features descriptors real-time lightweight cvpr-2024 torch-hub sparse-matching semi-dense-matching cpu gpu
3 sources
- readme: https://github.com/verlab/accelerated_features · fetched 2026-08-28 · d7520ae9342a
- homepage: https://www.verlab.dcc.ufmg.br/descriptors/xfeat_cvpr24 · fetched 2026-08-29 · a9b5b0a23db5
- site_page: https://www.verlab.dcc.ufmg.br/about-us · fetched 2026-08-29 · 6bb4b1a6b6f6
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| verlab/accelerated_features | main | 16 |
For agents
markdown · JSON · MCP: product_card(name="verlab/accelerated_features")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem