Hierarchical Connectivity-Centered Clustering for Unsupervised Domain Adaptation on Person Re-Identification

• Published in: IEEE transactions on image processing Vol. 30; pp. 6715 - 6729
• Main Authors: Bai, Yan, Wang, Ce, Lou, Yihang, Liu, Jun, Duan, Ling-Yu
• Format: Journal Article
• Language: English
• Published: New York IEEE 2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptation; Adaptation models; Clustering; Clustering methods; Connectivity; Data mining; Domains; Feature extraction; graph convolutional networks; Graph representations; Graph theory; Graphical representations; Knowledge management; Labels; person re-identification; Training; Training data; Unsupervised domain adaptation; Visualization

Unsupervised domain adaptation (UDA) on person Re-Identification (ReID) aims to transfer the knowledge from a labeled source domain to an unlabeled target domain. Recent works mainly optimize the ReID models with pseudo labels generated by unsupervised clustering on the target domain. However, the p...