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Unsupervised Person Re-ID Noise Purification by bkdaddin is a document available to read on EtoBox.

This article proposes a method for unsupervised person re-identification that aims to purify feature and label noise. It introduces two purification modules: 1) A multi-view feature module that enriches the global feature representation with additional local view features. 2) A knowledge distillation module that trains a teacher model on noisy pseudo labels to guide learning and reduce interference from label noise. The purification modules are integrated into an existing cluster contrast learning framework

Author
bkdaddin
Language
EN