Unsupervised Horizontal Pyramid Similarity Learning for Cross-domain Adaptive Person Re-identification

• Published in: IEEE access Vol. 9; p. 1
• Main Authors: Dong, Wenhui, Qu, Peishu, Liu, Chunsheng, Tang, Yanke, Gai, Ning
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptation models; Algorithms; Bins; Clustering; Data models; Deep learning; Domains; Feature extraction; Feature maps; Generative adversarial networks; Horizontal pyramid similarity learning; Learning; Person re-identification; Similarity; Surveillance; Training; Unsupervised cross domain adaption; Unsupervised deep learning

Although person re-identification has made great progress, unsupervised cross-domain adaptive person re-identification is still a challenging problem. With no labeled data in target domain, the performance may have a significant drop. In this paper, we propose an unsupervised cross-domain adaptive p...