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Found 2 papers, 1 papers with code
A High-Accuracy Unsupervised Person Re-identification Method Using Auxiliary Information Mined from Datasets
Combined with auxiliary information exploiting modules, our methods achieve mAP of 89. 9% on DukeMTMC, where TOC, STS and SCP all contributed considerable performance improvements.
Ranked #1 on
Unsupervised Person Re-Identification
on MARS
A Free Lunch to Person Re-identification: Learning from Automatically Generated Noisy Tracklets
Extensive experiments on MARS with various manually generated noises show the effectiveness of the proposed framework.
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