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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence

Multi-Spectral Vehicle Re-Identification: A Challenge

February 1, 2023

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Authors

Hongchao Li

Anhui University


Chenglong Li

Anhui University


Xianpeng Zhu

Anhui University


Aihua Zheng

Anhui University


Bin Luo

Anhui University


DOI:

10.1609/aaai.v34i07.6796


Abstract:

Vehicle re-identification (Re-ID) is a crucial task in smart city and intelligent transportation, aiming to match vehicle images across non-overlapping surveillance camera views. Currently, most works focus on RGB-based vehicle Re-ID, which limits its capability of real-life applications in adverse environments such as dark environments and bad weathers. IR (Infrared) spectrum imaging offers complementary information to relieve the illumination issue in computer vision tasks. Furthermore, vehicle Re-ID suffers a big challenge of the diverse appearance with different views, such as trucks. In this work, we address the RGB and IR vehicle Re-ID problem and contribute a multi-spectral vehicle Re-ID benchmark named RGBN300, including RGB and NIR (Near Infrared) vehicle images of 300 identities from 8 camera views, giving in total 50125 RGB images and 50125 NIR images respectively. In addition, we have acquired additional TIR (Thermal Infrared) data for 100 vehicles from RGBN300 to form another dataset for three-spectral vehicle Re-ID. Furthermore, we propose a Heterogeneity-collaboration Aware Multi-stream convolutional Network (HAMNet) towards automatically fusing different spectrum features in an end-to-end learning framework. Comprehensive experiments on prevalent networks show that our HAMNet can effectively integrate multi-spectral data for robust vehicle Re-ID in day and night. Our work provides a benchmark dataset for RGB-NIR and RGB-NIR-TIR multi-spectral vehicle Re-ID and a baseline network for both research and industrial communities. The dataset and baseline codes are available at: https://github.com/ttaalle/multi-modal-vehicle-Re-ID.

Topics: AAAI

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HOW TO CITE:

Hongchao Li||Chenglong Li||Xianpeng Zhu||Aihua Zheng||Bin Luo Multi-Spectral Vehicle Re-Identification: A Challenge Proceedings of the AAAI Conference on Artificial Intelligence (2020) 11345-11353.

Hongchao Li||Chenglong Li||Xianpeng Zhu||Aihua Zheng||Bin Luo Multi-Spectral Vehicle Re-Identification: A Challenge AAAI 2020, 11345-11353.

Hongchao Li||Chenglong Li||Xianpeng Zhu||Aihua Zheng||Bin Luo (2020). Multi-Spectral Vehicle Re-Identification: A Challenge. Proceedings of the AAAI Conference on Artificial Intelligence, 11345-11353.

Hongchao Li||Chenglong Li||Xianpeng Zhu||Aihua Zheng||Bin Luo. Multi-Spectral Vehicle Re-Identification: A Challenge. Proceedings of the AAAI Conference on Artificial Intelligence 2020 p.11345-11353.

Hongchao Li||Chenglong Li||Xianpeng Zhu||Aihua Zheng||Bin Luo. 2020. Multi-Spectral Vehicle Re-Identification: A Challenge. "Proceedings of the AAAI Conference on Artificial Intelligence". 11345-11353.

Hongchao Li||Chenglong Li||Xianpeng Zhu||Aihua Zheng||Bin Luo. (2020) "Multi-Spectral Vehicle Re-Identification: A Challenge", Proceedings of the AAAI Conference on Artificial Intelligence, p.11345-11353

Hongchao Li||Chenglong Li||Xianpeng Zhu||Aihua Zheng||Bin Luo, "Multi-Spectral Vehicle Re-Identification: A Challenge", AAAI, p.11345-11353, 2020.

Hongchao Li||Chenglong Li||Xianpeng Zhu||Aihua Zheng||Bin Luo. "Multi-Spectral Vehicle Re-Identification: A Challenge". Proceedings of the AAAI Conference on Artificial Intelligence, 2020, p.11345-11353.

Hongchao Li||Chenglong Li||Xianpeng Zhu||Aihua Zheng||Bin Luo. "Multi-Spectral Vehicle Re-Identification: A Challenge". Proceedings of the AAAI Conference on Artificial Intelligence, (2020): 11345-11353.

Hongchao Li||Chenglong Li||Xianpeng Zhu||Aihua Zheng||Bin Luo. Multi-Spectral Vehicle Re-Identification: A Challenge. AAAI[Internet]. 2020[cited 2023]; 11345-11353.


ISSN: 2374-3468


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