vcl-seoultech/SirNet

Sampling Agnostic Feature Representation for Long-Term Person Re-identification

27
/ 100
Experimental

This tool helps security or surveillance professionals accurately identify individuals over extended periods, even when their appearance changes. It takes video feeds or image datasets of people and produces a reliable identification for each person, regardless of variations in clothing or other factors that typically make long-term tracking difficult. It's designed for anyone managing large-scale video surveillance or person tracking systems.

No commits in the last 6 months.

Use this if you need to consistently recognize the same person across different times and locations, despite changes in their clothing or appearance.

Not ideal if your primary need is real-time, short-term identification in highly controlled environments without significant appearance changes.

person-reidentification video-surveillance security-systems identity-tracking facial-recognition
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 6 / 25

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Stars

12

Forks

1

Language

Python

License

Last pushed

Feb 26, 2023

Commits (30d)

0

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