Vehicle re-identification is the task of identifying the same vehicle in different environments and from different angles and cameras. It is more challenging than re-identification of humans: 1)small differences between vehicles of the same model make it difficult to capture their subtle characteristics; 2)vehicles of different types and colors may have similar characteristics from different viewpoints or external conditions. To address these challenges, we propose a TVG-ReID network, using a Transformer network to enhance features extracted from a CNN backbone network. A vehicle knowledge graph transfer method(Vehicle-Graph) is proposed, which treats each vehicle as a node in a graph, where simple information is transmitted through edges to constrain the distance of the nodes in a metric learning manner. Experiments on two vehicle re-identification datasets demonstrate the good performance of our proposed model.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    TVG-ReID: Transformer-Based Vehicle-Graph Re-Identification


    Contributors:
    Li, Zhiwei (author) / Zhang, Xinyu (author) / Tian, Chi (author) / Gao, Xin (author) / Gong, Yan (author) / Wu, Jiani (author) / Zhang, Guoying (author) / Li, Jun (author) / Liu, Huaping (author)

    Published in:

    Publication date :

    2023-11-01


    Size :

    4284845 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Estimating vehicle fuel Reid vapor pressure

    DUDAR AED M / JENTZ ROBERT ROY | European Patent Office | 2017

    Free access



    UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-identification in Video Imagery

    Organisciak, Daniel / Poyser, Matthew / Alsehaim, Aishah et al. | ArXiv | 2021

    Free access

    Douglas Reid Skinner

    Fazzini, Marco | DOAJ | 2020

    Free access