Trajectory-text retrieval model based on graph neural network

Hanchao Tang; Licai Wang; Qibin Luo

doi:10.1117/12.2660180

3 February 2023 Trajectory-text retrieval model based on graph neural network

Hanchao Tang, Licai Wang, Qibin Luo

Proceedings Volume 12511, Third International Conference on Computer Vision and Data Mining (ICCVDM 2022); 1251134 (2023) https://doi.org/10.1117/12.2660180
Event: Third International Conference on Computer Vision and Data Mining (ICCVDM 2022), 2022, Hulun Buir, China

Abstract

Cross-modal retrieval has been widely used in the Vision-Language field and has achieved many results, but there is a lack of research in the trajectory-text field. At the same time, the current popular cross-modal retrieval models not only lack fine-grained semantic alignment between different modalities, but also ignore the influence of the grammatical structure of the text on the retrieval effect. To solve the above problems, this paper proposes a dual-stream trajectory text retrieval model combined with graph neural network, combining local and global two cross-modal interaction methods: (1) Local alignment, encoding trajectory points and words respectively after passing through the masking module. Semantic alignment. (2) Global alignment, introducing momentum contrastive learning to achieve trajectory and text retrieval learning. Experimental results show that this hierarchical matching method not only retains the efficient performance of the dual-stream model, but also has higher accuracy than other cross-modal retrieval models, and its R@1 value on the dataset is improved by 3.2%-4.7%.

Citation Download Citation

Hanchao Tang, Licai Wang, and Qibin Luo "Trajectory-text retrieval model based on graph neural network", Proc. SPIE 12511, Third International Conference on Computer Vision and Data Mining (ICCVDM 2022), 1251134 (3 February 2023); https://doi.org/10.1117/12.2660180

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
8 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Data modeling

Feature extraction

Neural networks

Computer programming

Transformers

Performance modeling

Process modeling

Show All Keywords

Keywords/Phrases

Search In:

Publication Years