Journal of Computer Applications ›› 2022, Vol. 42 ›› Issue (6): 1884-1891.DOI: 10.11772/j.issn.1001-9081.2021040544
Special Issue: 人工智能
• Artificial intelligence • Previous Articles Next Articles
Tingping ZHANG1, Cong SHUAI1(), Jianxi YANG1, Junzhi ZOU2, Chaoshun YU3, Lifang DU3
Received:
2021-04-12
Revised:
2021-08-10
Accepted:
2021-08-11
Online:
2022-06-22
Published:
2022-06-10
Contact:
Cong SHUAI
About author:
ZHANG Tingping, born in 1978, Ph. D., professor. Her research interests include evaluation of node importance in complex networks.Supported by:
张廷萍1, 帅聪1(), 杨建喜1, 邹俊志2, 郁超顺3, 杜利芳3
通讯作者:
帅聪
作者简介:
张廷萍(1978—),女,贵州遵义人,教授,博士,主要研究方向:复杂网络节点重要度评估基金资助:
CLC Number:
Tingping ZHANG, Cong SHUAI, Jianxi YANG, Junzhi ZOU, Chaoshun YU, Lifang DU. Re-identification of vehicles based on joint stripe relations[J]. Journal of Computer Applications, 2022, 42(6): 1884-1891.
张廷萍, 帅聪, 杨建喜, 邹俊志, 郁超顺, 杜利芳. 基于联合条纹关系的车辆重识别[J]. 《计算机应用》唯一官方网站, 2022, 42(6): 1884-1891.
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URL: https://www.joca.cn/EN/10.11772/j.issn.1001-9081.2021040544
特征图分割方向 | mAP | Rank1 | Rank5 |
---|---|---|---|
仅水平分支 | 78.7 | 94.4 | 96.7 |
仅竖直分支 | 82.1 | 95.6 | 98.5 |
两个分支 | 84.1 | 96.6 | 98.4 |
Tab.1 Effect of feature map segmentation directions on model performance
特征图分割方向 | mAP | Rank1 | Rank5 |
---|---|---|---|
仅水平分支 | 78.7 | 94.4 | 96.7 |
仅竖直分支 | 82.1 | 95.6 | 98.5 |
两个分支 | 84.1 | 96.6 | 98.4 |
分割数目 | mAP | Rank1 | Rank5 |
---|---|---|---|
2 | 76.5 | 89.2 | 93.6 |
4 | 83.1 | 95.3 | 98.4 |
6 | 84.1 | 96.6 | 98.4 |
8 | 82.6 | 95.4 | 98.1 |
Tab.2 Effect of number of feature map segmentation on model performance
分割数目 | mAP | Rank1 | Rank5 |
---|---|---|---|
2 | 76.5 | 89.2 | 93.6 |
4 | 83.1 | 95.3 | 98.4 |
6 | 84.1 | 96.6 | 98.4 |
8 | 82.6 | 95.4 | 98.1 |
激活值数目 | mAP | Rank1 | Rank5 |
---|---|---|---|
1 | 77.5 | 94.6 | 98.2 |
2 | 79.4 | 94.4 | 97.8 |
3 | 84.1 | 96.6 | 98.4 |
4 | 83.6 | 96.6 | 95.5 |
Tab.3 Effect of number of activation values on model performance
激活值数目 | mAP | Rank1 | Rank5 |
---|---|---|---|
1 | 77.5 | 94.6 | 98.2 |
2 | 79.4 | 94.4 | 97.8 |
3 | 84.1 | 96.6 | 98.4 |
4 | 83.6 | 96.6 | 95.5 |
依次添加的模块 | mAP | Rank1 | Rank5 |
---|---|---|---|
Baseline | 77.0 | 95.0 | 97.9 |
多激活值模块 | 80.2 | 95.6 | 98.1 |
关系描述模块 | 83.5 | 96.2 | 97.9 |
批量归一化模块 | 84.1 | 96.6 | 98.4 |
Tab.4 Ablation experiment
依次添加的模块 | mAP | Rank1 | Rank5 |
---|---|---|---|
Baseline | 77.0 | 95.0 | 97.9 |
多激活值模块 | 80.2 | 95.6 | 98.1 |
关系描述模块 | 83.5 | 96.2 | 97.9 |
批量归一化模块 | 84.1 | 96.6 | 98.4 |
算法 | mAP | Rank1 | Rank5 |
---|---|---|---|
GS-TRE[ | 59.4 | 96.2 | 98.9 |
VANet[ | 66.3 | 89.7 | 95.9 |
PNVR[ | 74.3 | 94.3 | 98.7 |
MRL[ | 78.5 | 94.3 | 99.0 |
SAN[ | 72.5 | 93.3 | 97.1 |
EVER[ | 79.9 | 95.9 | 98.2 |
VehicleNet[ | 83.4 | 96.7 | — |
本文算法 | 84.1 | 96.6 | 98.4 |
本文算法+Re-ranking | 86.0 | 97.4 | 98.4 |
Tab.5 Comparison of different algorithms on VeRi-776 dataset
算法 | mAP | Rank1 | Rank5 |
---|---|---|---|
GS-TRE[ | 59.4 | 96.2 | 98.9 |
VANet[ | 66.3 | 89.7 | 95.9 |
PNVR[ | 74.3 | 94.3 | 98.7 |
MRL[ | 78.5 | 94.3 | 99.0 |
SAN[ | 72.5 | 93.3 | 97.1 |
EVER[ | 79.9 | 95.9 | 98.2 |
VehicleNet[ | 83.4 | 96.7 | — |
本文算法 | 84.1 | 96.6 | 98.4 |
本文算法+Re-ranking | 86.0 | 97.4 | 98.4 |
算法 | 小型 | 中型 | 大型 | |||
---|---|---|---|---|---|---|
Rank1 | Rank5 | Rank1 | Rank5 | Rank1 | Rank5 | |
GS-TRE[ | 75.9 | 84.2 | 74.8 | 83.6 | 74.0 | 82.7 |
PRN[ | 78.9 | 94.8 | 74.9 | 92.0 | 71.5 | 88.4 |
PNVR[ | 78.4 | 92.3 | 75.0 | 88.3 | 74.2 | 86.4 |
VANet[ | 83.2 | 95.9 | 81.1 | 94.7 | 77.2 | 86.7 |
MRL[ | 84.8 | 96.9 | 80.9 | 94.1 | 78.4 | 92.1 |
EVER[ | 84.5 | 96.4 | 79.7 | 94.7 | 77.4 | 91.8 |
SAN[ | 79.7 | 94.3 | 78.4 | 91.3 | 75.3 | 88.3 |
VehicleNet[ | 83.6 | 96.8 | 81.3 | 93.6 | 79.4 | 92.0 |
本文算法 | 87.2 | 98.4 | 82.4 | 96.4 | 80.1 | 94.4 |
Tab.6 Comparison of different algorithms on VehicleID dataset
算法 | 小型 | 中型 | 大型 | |||
---|---|---|---|---|---|---|
Rank1 | Rank5 | Rank1 | Rank5 | Rank1 | Rank5 | |
GS-TRE[ | 75.9 | 84.2 | 74.8 | 83.6 | 74.0 | 82.7 |
PRN[ | 78.9 | 94.8 | 74.9 | 92.0 | 71.5 | 88.4 |
PNVR[ | 78.4 | 92.3 | 75.0 | 88.3 | 74.2 | 86.4 |
VANet[ | 83.2 | 95.9 | 81.1 | 94.7 | 77.2 | 86.7 |
MRL[ | 84.8 | 96.9 | 80.9 | 94.1 | 78.4 | 92.1 |
EVER[ | 84.5 | 96.4 | 79.7 | 94.7 | 77.4 | 91.8 |
SAN[ | 79.7 | 94.3 | 78.4 | 91.3 | 75.3 | 88.3 |
VehicleNet[ | 83.6 | 96.8 | 81.3 | 93.6 | 79.4 | 92.0 |
本文算法 | 87.2 | 98.4 | 82.4 | 96.4 | 80.1 | 94.4 |
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