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App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 7

Paper-cutting image classification enhanced by clip text features

Zhang Xinsheng1,2
Chen Ding1
Qin Yibing1
1. School of Information & Control Engineering, Xi'an University of Architecture & Technology, Xi'an 710055, China
2. School of Management, Xi'an University of Architecture & Technology, Xi'an 710055, China
DOI: 10.19734/j.issn.1001-3695.2024.11.0485

Abstract

To address the challenges of large modality gaps between text and image features and insufficient class prototype representation in paper-cut image classification, this paper proposed a CLIP-based text feature enhancement method (CLIP Visual Text Enhancer, C-VTE) . The method utilized manually designed prompt templates to extract text features and developed a visual-text enhancement module that integrates proportional residual connections to fuse image and text features, effectively reducing modality discrepancies and enhancing category feature representation. Experiments on a paper-cut dataset and four public datasets including Caltech101 validated its effectiveness. For base-class classification on the paper-cut dataset, C-VTE achieved 72.51% average accuracy, outperforming existing methods by 3.14 percentage points. In few-shot classification tasks on public datasets, it attained 84.78% average accuracy with a 2.45 percentage-point improvement. Ablation experiments demonstrate that both the modality fusion module and proportional residual components contribute significantly to performance improvement. The method offers novel insights for efficient adaptation of vision-language models in downstream classification tasks, particularly suited for few-shot learning and base-class dominated scenarios.

Foundation Support

陕西省重点产业链(群)创新项目(2022ZDLGY06-04)
泛在信息社会下AI生成式虚假信息风险感知及治理路径研究教育部人文社科规划基金项目(24YJA630129)
AIGC时代下生成式虚假信息风险感知及治理路径研究陕西省社会科学基金项目(2024R083)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.11.0485
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 7

Publish History

[2025-03-13] Accepted Paper

Cite This Article

张新生, 陈鼎, 秦一冰. 基于CLIP文本特征增强的剪纸图像分类 [J]. 计算机应用研究, 2025, 42 (7). (2025-03-14). https://doi.org/10.19734/j.issn.1001-3695.2024.11.0485. (Zhang Xinsheng, Chen Ding, Qin Yibing. Paper-cutting image classification enhanced by clip text features [J]. Application Research of Computers, 2025, 42 (7). (2025-03-14). https://doi.org/10.19734/j.issn.1001-3695.2024.11.0485. )

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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