Abstract:Although clustering-based unsupervised domain adaptive person re-identification has achieved promising progress, negative influence of noisy pseudo labels is still unsolved. Training model with noisy labeled data will mislead feature representation and ultimately affect the improvement of model performance. To tackle the above problem, we propose a dual pseudo label refinement framework for unsupervised domain adaptive person re-identification. It has two pseudo label refinement modules, one learns cross consi… Show more
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