In accordance with regulations and requirements, the editorial department's website domain has been changed to arocmag.cn. The original domain (arocmag.com) has been redirecting to new domain since Jan. 1st, 2025.
See More
App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 7

Information complementarity and cross-attention for cross-modal retrieval

Wang Dan
Zhang Feng
Zhang Hui
Zhu Jie
College of Mathematics & Information Science, Hebei University, Baoding Hebei 071002, China
DOI: 10.19734/j.issn.1001-3695.2025.01.0003

Abstract

With the rapid growth of multimodal data on the internet, cross-modal retrieval technology has attracted widespread attention. However, some multimodal data often lack semantic information, which leads to the inability of models to accurately extract the inherent semantic features. Additionally, some multimodal data contain redundant information unrelated to semantics, which interferes with the model extraction of key information. To address this, a cross-modal retrieval method based on information complementarity and cross-attention (ICCA) is proposed. The method uses a Graph Convolutional Network (GCN) to model the relationships between multi-labels and data, supplementing the missing semantic information in multimodal data and the missing sample detail information in multi-labels. Moreover, a cross-attention submodule uses multi-label information to filter out the redundant semantic-irrelevant data. To achieve better matching of semantically similar images and texts in the common representation space, a semantic matching loss is proposed. This loss integrates multi-label embeddings into the image-text matching process, further enhancing the semantic quality of the common representation. Experimental results on three widely used datasets NUS-WIDE, MIRFlickr-25K, and MS-COCO demonstrate that ICCA achieves mean Average Precision (mAP) values of 0.808, 0.859, and 0.837, respectively, significantly outperforming existing methods.

Foundation Support

国家自然科学基金项目(61802269)
河北省自然科学基金项目(F2022511001)
河北省高等学校科学技术研究项目(ZC2022070)
河北大学高层次人才科研启动项目(521100223212)
河北省创新能力提升计划—科技平台项目(22567623H)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.01.0003
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 7

Publish History

[2025-03-14] Accepted Paper

Cite This Article

王丹, 张峰, 张辉, 等. 基于信息互补与交叉注意力的跨模态检索方法 [J]. 计算机应用研究, 2025, 42 (7). (2025-03-14). https://doi.org/10.19734/j.issn.1001-3695.2025.01.0003. (Wang Dan, Zhang Feng, Zhang Hui, et al. Information complementarity and cross-attention for cross-modal retrieval [J]. Application Research of Computers, 2025, 42 (7). (2025-03-14). https://doi.org/10.19734/j.issn.1001-3695.2025.01.0003. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)