NUISTGY/Deep-High-Resolution-Representation-Learning-for-Cross-Resolution-Person-Re-identification
Journal of IEEE TIP
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.
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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.
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Jupyter Notebook
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GPL-3.0
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Last pushed
Mar 15, 2022
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