URRNet: A Unified Relational Reasoning Network for Vehicle Re-Identification-Reference-Cited by-同舟云学术

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URRNet: A Unified Relational Reasoning Network for Vehicle Re-Identification

Published:2023-09 Issue:9 Volume:72 Page:11156-11168
ISSN:0018-9545
Container-title:IEEE Transactions on Vehicular Technology
language:
Short-container-title:IEEE Trans. Veh. Technol.

Author:

Qian Jiuchao¹^ORCID,Pan Minting¹,Tong Wei²^ORCID,Law Rob³^ORCID,Wu Edmond Q.⁴^ORCID

Affiliation:

1. School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China

2. School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, China

3. Asia-Pacific Academy of Economics and Management, University of Macau, Macau, China

4. Department of Automation, Shanghai Jiao Tong University, Shanghai, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Aerospace Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/25/10254672/10086683.pdf?arnumber=10086683

Reference48 articles.

1. Trends in Vehicle Re-Identification Past, Present, and Future: A Comprehensive Review

2. A vehicle license plate detection method using region and edge based methods

3. Deep Quadruplet Appearance Learning for Vehicle Re-Identification

4. Soft-Weighted-Average Ensemble Vehicle Detection Method Based on Single-Stage and Two-Stage Deep Learning Models

5. Vehicle Detection and Disparity Estimation Using Blended Stereo Images

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1. TANet: Text region attention learning for vehicle re-identification;Engineering Applications of Artificial Intelligence;2024-07

2. Dual-Level Viewpoint-Learning for Cross-Domain Vehicle Re-Identification;Electronics;2024-05-08

3. Multi-axis interactive multidimensional attention network for vehicle re-identification;Image and Vision Computing;2024-04

4. Unsupervised Video Summarization Based on the Diffusion Model of Feature Fusion;IEEE Transactions on Computational Social Systems;2024

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