vcl-seoultech/SirNet
Sampling Agnostic Feature Representation for Long-Term Person Re-identification
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.
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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.
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Language
Python
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Last pushed
Feb 26, 2023
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