@inproceedings{90e02bde94d8476dbbceb0711ccb08ff,
title = "Re-identifying Pedestrians via Part Based Method",
abstract = "Person re-identification (Re-id) has received more and more attention due to its wide applications and various approaches were proposed to solve the challenging task. In this paper, we adopt part-based model as the main method to perform person Re-id on the self-made dataset. In order to improve accuracy, transfer learning is applied in both a direct and indirect way by leveraging original public dataset Market-1501 and its transferred counterpart respectively. The transferred dataset is obtained by making the pedestrians in the original public dataset show similar styles to those of the self-made dataset while keeping their identities unchanged. Experimental results demonstrate the effectiveness of transfer learning and the superiority of applying transfer learning indirectly against applying transfer learning directly.",
keywords = "Convolutional Neural Networks, Generative adversarial Networks, PCB, Person Re-identification",
author = "Pingli Lu and Yafei Wei and Xiaowei Gu and Wei Han and Chao Li",
note = "Publisher Copyright: {\textcopyright} 2020 Technical Committee on Control Theory, Chinese Association of Automation.; 39th Chinese Control Conference, CCC 2020 ; Conference date: 27-07-2020 Through 29-07-2020",
year = "2020",
month = jul,
doi = "10.23919/CCC50068.2020.9189140",
language = "English",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "7118--7122",
editor = "Jun Fu and Jian Sun",
booktitle = "Proceedings of the 39th Chinese Control Conference, CCC 2020",
address = "United States",
}