人工智能在视觉设计领域研究热点的可视化分析

陈航宇; 潘晓宇; 赵东民

doi:10.19554/j.cnki.1001-3563.2025.24.043

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包装工程（设计栏目） ›› 2025, Vol. 46 ›› Issue (24) : 507-516. DOI: 10.19554/j.cnki.1001-3563.2025.24.043

设计研讨

人工智能在视觉设计领域研究热点的可视化分析

陈航宇^1,2, 潘晓宇³, 赵东民^1,*

作者信息 +

Visual Analysis of Research Hotspots of Artificial Intelligence in Visual Design Field

CHEN Hangyu^1,2, PAN Xiaoyu³, CHO Dongmin^1,*

Author information +

文章历史 +

摘要

目的深入分析人工智能在视觉设计领域的文献,揭示研究热点和主题演化,为理解该领域的技术进步和未来发展趋势提供重要的学术参考和实践指导。方法将LDA（潜在狄利克雷）主题建模算法与TexSmart系统的细粒度命名实体识别方法进行结合,来提升建模主题的质量,通过可视化技术,对2002—2024年人工智能在视觉设计领域的研究文献进行了深入的主题建模和演化分析。研究利用Web of Science数据库,通过精心设计的检索式,获取了大量文献数据,并通过严格的数据清洗和预处理步骤,为LDA分析提供了高质量的输入。结果揭示了人工智能在视觉设计领域研究的6个主要热点：图像识别与分类、生成对抗网络（GANs）、3D视觉与重建、扩散模型（Diffusion Models）、视觉语言模型（VLMs）、动态和交互式设计。结论研究进一步通过LDA法分析了研究主题随时间的演化趋势,明确了人工智能在视觉设计领域的研究主题经历了从单一的统计学习向与多个前沿领域相结合的转变。

Abstract

The work aims to conduct an in-depth analysis of the literature on artificial intelligence in the field of visual design and reveal research hotspots and the evolution of topics, providing important academic references and practical guidance for understanding the technological progress and future development trends in this field. The LDA (latent Delicacy Area) topic modelling algorithm was combined with the fine-grained named entity recognition method of the TexSmart system to improve the quality of the modelled topics. Then, an in-depth topic modelling and evolution analysis of the research literature on AI in the field of visual design for the period of 2002-2024 was carried out through visualization techniques. The study utilized the Web of Science database to acquire a large amount of literature data through a well-designed search formula, and provided high-quality inputs for the LDA analysis through rigorous data cleaning and preprocessing steps. The results revealed six major hotspots in the research of artificial intelligence in the field of visual design: image recognition and classification, generative adversarial networks (GANs), 3D vision and reconstruction, diffusion models, visual language models (VLMs) and dynamic and interactive design. The study further analyses the evolutionary trend of the research topics over time through the LDA method, and clarifies that the research topics of AI in the field of visual design have experienced a shift from a single statistical learning to a combination with multiple cutting-edge fields.

导出引用1

陈航宇, 潘晓宇, 赵东民. 人工智能在视觉设计领域研究热点的可视化分析[J]. 包装工程. 2025, 46(24): 507-516 https://doi.org/10.19554/j.cnki.1001-3563.2025.24.043

CHEN Hangyu, PAN Xiaoyu, CHO Dongmin. Visual Analysis of Research Hotspots of Artificial Intelligence in Visual Design Field[J]. Packaging Engineering. 2025, 46(24): 507-516 https://doi.org/10.19554/j.cnki.1001-3563.2025.24.043

中图分类号： TB472 TP399

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