Institute of Computing Technology, Chinese Academy IR
Part alignment network for vehicle re-identification | |
Chen, Yucheng1,2; Ma, Bingpeng2; Chang, Hong1,2 | |
2020-12-22 | |
发表期刊 | NEUROCOMPUTING |
ISSN | 0925-2312 |
卷号 | 418页码:114-125 |
摘要 | Vehicle re-identification (re-ID) has numerous applications in real life, such as video surveillance, information retrieval, and public security. However, it suffers from the misalignment of vehicles, which is a critical problem caused by inaccurate detection and different views. This paper proposes a novel network named Part Alignment Network (PAN) which can properly handle the misalignment of vehicles. It is therefore adapted to the vehicle re-ID task, avoiding the use of any additional pre-processing steps such as the annotation of vehicle key points and part segmentation by hand. In PAN, cross-correlation is adopted to the alignment of vehicle parts. Then, an effective network architecture is designed to extract the discriminative aligned features. By combining complementary aligned features and original features, more robust feature representations are learned. To show the effectiveness of PAN, this paper conducts experiments on three vehicle re-ID databases (VD1, VD2, and VehicleID), on which it improves the current state-of-the-art performance. (c) 2020 Elsevier B.V. All rights reserved. |
关键词 | Vehicle re-identification Part alignment Cross-correlation |
DOI | 10.1016/j.neucom.2020.08.016 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | Natural Science Foundation of China (NSFC)[61876171] ; Natural Science Foundation of China (NSFC)[61976203] ; Beijing Municipal Science and Technology Program[Z181100003918012] ; Fundamental Research Funds for the Central Universities |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence |
WOS记录号 | WOS:000589911100010 |
出版者 | ELSEVIER |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.204/handle/2XEOYT63/16120 |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Ma, Bingpeng |
作者单位 | 1.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, CAS, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
推荐引用方式 GB/T 7714 | Chen, Yucheng,Ma, Bingpeng,Chang, Hong. Part alignment network for vehicle re-identification[J]. NEUROCOMPUTING,2020,418:114-125. |
APA | Chen, Yucheng,Ma, Bingpeng,&Chang, Hong.(2020).Part alignment network for vehicle re-identification.NEUROCOMPUTING,418,114-125. |
MLA | Chen, Yucheng,et al."Part alignment network for vehicle re-identification".NEUROCOMPUTING 418(2020):114-125. |
条目包含的文件 | 条目无相关文件。 |
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