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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 1
10-20

Research advances in explainable visual question answering

Zhang Yifei1
Meng Chunyun1
Jiang Zhou2
Luan Li3
Ernest Domanaanmwi Ganaa4
1. School of Economics & Management, Jiangsu University of Science & Technology, Zhenjiang Jiangsu 212100, China
2. School of Computer Science & Communication Engineering, Jiangsu University, Zhenjiang Jiangsu 212013, China
3. School of Public Affairs, University of Science & Technology of China, Hefei 230026, China
4. Faculty of Applied Science & Technology, Hilla Limann Technical University, Wa 00233, Ghana
DOI: 10.19734/j.issn.1001-3695.2023.05.0181

Abstract

In the context of visual question answering(VQA) tasks, "explainability" refers to the various ways in which researchers can explain why a model works in a given task. The lack of explainability of some existing VQA models has led to a lack of assurance that the models can be used safely in real-life applications, especially in fields such as autonomous driving and healthcare. This would raise ethical and moral issues that hinder their implementation in industry. This paper introduced various implementations for enhancing explainability in VQA tasks and categorized them into four main categories: image interpretation, text interpretation, multi-modal interpretation, modular interpretation, and graph interpretation. This paper discussed the characteristics of each approach, and further presented the subdivisions for some of them. Furthermore, it presented several VQA datasets that aimed to enhance explainability. These datasets primarily focused on incorporating external know-ledge bases and annotating image information to improve explainability. In summary, this paper provided an overview of exis-ting commonly used interpretable methods for VQA tasks and proposed future research directions based on the identified shortcomings of the current approaches.

Foundation Support

国家社科基金重点项目(16AJL008)
江苏省社科基金青年项目(22EYC001)
江苏高校哲学社会科学研究一般项目(2019SJA1927)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.05.0181
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 1
Section: Survey
Pages: 10-20
Serial Number: 1001-3695(2024)01-002-0010-11

Publish History

[2023-07-14] Accepted Paper
[2024-01-05] Printed Article

Cite This Article

张一飞, 孟春运, 蒋洲, 等. 可解释的视觉问答研究进展 [J]. 计算机应用研究, 2024, 41 (1): 10-20. (Zhang Yifei, Meng Chunyun, Jiang Zhou, et al. Research advances in explainable visual question answering [J]. Application Research of Computers, 2024, 41 (1): 10-20. )

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.

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