基于CiteSpace的国内虚拟试衣技术可视化分析OA

In recent years,virtual try-on technology has attracted extensive attention and research as an important innovation in the field of digital apparel.In December 2018,the Ministry of Industry and Information Technology of the People's Republic of China issued the Guiding Opinions on Accelerating the Development of the Virtual Reality Industry,which explicitly encouraged innovation and application of virtual reality technologies.Furthermore,the Government Work Report released in 2024 emphasized the promotion of innovation-driven development of the digital economy,the deep integration of the digital economy with the real economy,the strengthened application of big data and artificial intelligence technologies,and the implementation of the"Artificial Intelligence Plus"initiative.Under this background,research on virtual try-on technology has gradually deepened,becoming one of the key directions for promoting the digital transformation and upgrading of the apparel industry. To gain an in-depth understanding of the research status of virtual try-on technology in the textile and apparel field,this study employs CiteSpace as a visual bibliometric analysis tool.A total of 758 domestic publications related to virtual try-on technology,retrieved from China National Knowledge Infrastructure(CNKI)and Web of Science(WoS)core collections,are selected as the research objects.Basic bibliometric information,including annual publication volume,research institutions,and source journals,is statistically analyzed to identify the distribution characteristics of virtual try-on research.Based on cooperation knowledge maps,the collaboration relationships among authors and institutions in the virtual try-on field are further examined.In addition,co-occurrence knowledge maps,clustering knowledge maps,burst keyword maps,and timeline knowledge maps are constructed to systematically summarize the research status,major hotspots,and future development trends of domestic virtual try-on technology over the past three decades.Different from traditional narrative review methods,this study introduces bibliometric analysis and knowledge mapping approaches to investigate domestic virtual try-on research based on data from the CNKI and WoS core collections.Through data visualization techniques,the research status,hotspot distribution,and evolutionary paths of the virtual try-on field are clearly presented.This method contributes to addressing the limitations of qualitative research in capturing macro-level trends and structural characteristics,and provides data-based support and developmental reference for subsequent research in this field.The analysis results show that the overall research intensity of virtual try-on technology exhibits an upward trend,transitioning from slow growth and steady development to a rapid surge in recent years.The main research hotspots are concentrated on modeling and simulation,image generation and virtual display,apparel marketing and retailing,as well as garment pattern design and ergonomics.Moreover,the frontier research trends in this field are closely related to artificial intelligence technologies,including deep learning,collision detection,generative adversarial networks,optical flow,and attention mechanisms. Future research is expected to focus on key artificial intelligence technologies,such as deep learning,collision detection,generative adversarial networks,optical flow,and attention mechanisms,with the aim of improving the realism of virtual display,enhancing image fidelity,and optimizing the efficiency of collision detection.Overall,although virtual try-on technology in China has developed rapidly,challenges related to the maturity of certain key technologies still exist,and further in-depth exploration is required to promote the sustainable development and practical application of virtual try-on technology in the digital apparel field.