Browse State-of-the-Art › Vehicle Color Recognition
Vehicle Color Recognition
2 papers with code · 0 benchmarks · 1 dataset archive 2025-07-28
Vehicle Color Recognition (VCR) involves developing a system to automatically identify and classify the color of vehicles from images or video footage. This task is essential for enhancing vehicle recognition systems, particularly in surveillance, law enforcement, and traffic management applications. The goal is to accurately categorize vehicles based on color, despite challenges such as varying lighting conditions, shadows, and low-resolution images.
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
1 dataset whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
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Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
2 shown of 2 papers with code (3 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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26 Oct 2015 8 repositories listedTo test our method, we use publicly vehicle color recognition dataset provided by Chen.
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21 Aug 2024 1 repository listedVehicle information recognition is crucial in various practical domains, particularly in criminal investigations.
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