NUISTGY/Deep-High-Resolution-Representation-Learning-for-Cross-Resolution-Person-Re-identification

Journal of IEEE TIP

39
/ 100
Emerging

This project helps security or surveillance professionals accurately identify individuals across camera feeds, even when image resolutions differ significantly. It takes video frames or images of people, some clear and high-resolution, others blurry and low-resolution, and outputs improved matches for individual identities. This tool is for security analysts, law enforcement, or anyone managing large-scale video surveillance systems.

No commits in the last 6 months.

Use this if you need to reliably track people across surveillance cameras that capture images at varying resolutions, such as when one camera is zoomed in and another is far away.

Not ideal if your primary need is general object detection or facial recognition rather than cross-resolution person re-identification.

surveillance security person-tracking identity-matching video-analytics
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 17 / 25

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Stars

23

Forks

8

Language

Jupyter Notebook

License

GPL-3.0

Last pushed

Mar 15, 2022

Commits (30d)

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