计算机工程与应用2026，Vol.62Issue(5)：314-325,12.DOI:10.3778/j.issn.1002-8331.2412-0241
轻量级深度特征交互融合的车辆重识别网络研究
Lightweight Deep Feature Interaction Fusion for Vehicle Re-Recognition Networks Research
摘要
Abstract
Vehicle re-recognition requires the model to focus on both the vehicle's overall outline and the vehicle's sub-tle local details at different stages to extract distinguishing features at a deeper level.To address the above problem,a pyra-mid branch with a lightweight large sense field is constructed,which significantly improves the performance of the back-bone network while introducing only less than 0.84 million additional parameters,which allows the model to focus on the global texture at the deeper level of the network.A backbone guided fusion module is proposed to enable the pyramid branches to learn effective feature representations,which can adaptively fuse the pyramid branch features with the back-bone features to help the pyramid branches learn effective information.In addition,an image deblurring technique is employed to preprocess the input features and combined with a parallel attention mechanism to enhance the attention to feature details.Experiments conducted on the Veri-776 and VehicleID datasets show that the proposed lightweight app-roach effectively improves vehicle re-recognition accuracy and generalization ability.关键词
车辆重识别(Vehicle Re-ID)/图像修复/轻量级特征金字塔分支/分支融合Key words
vehicle re-identification(Vehicle Re-ID)/image restoration/lightweight feature pyramid branch/branch fusion分类
信息技术与安全科学引用本文复制引用
徐岩,刘国荣,张晓迪,崔海青,薛威海,朱国生..轻量级深度特征交互融合的车辆重识别网络研究[J].计算机工程与应用,2026,62(5):314-325,12.基金项目
山东省研究生教育优质课程项目(SDYKC19083) （SDYKC19083）
山东省山东科技大学-海信(山东)冰箱有限公司研究生教育联合培养基地项目(SDYJD18027) （山东）
海信研究发展中心项目(SKDHKQ20230612,SKDHKQ20240464). （SKDHKQ20230612,SKDHKQ20240464）
