Hierarchical Clustering With Hard-Batch Triplet Loss for Person Re-Identification
Hierarchical Clustering With Hard-Batch Triplet Loss for Person Re-Identification
For clustering-guided fully unsupervised person reidentification (re-ID) methods, the quality of pseudo labels generated by clustering directly decides the model performance. In order to improve the quality of pseudo labels in existing methods, we propose the HCT method which combines hierarchical clustering with hard-batch triplet loss. The key idea of …