Jing Zhu, Chuanjiang Hu, Edris Khezri, Mohd Mustafa Mohd Ghazali
{"title":"边缘智能辅助大型模型动画设计:一项调查","authors":"Jing Zhu, Chuanjiang Hu, Edris Khezri, Mohd Mustafa Mohd Ghazali","doi":"10.1186/s13677-024-00601-3","DOIUrl":null,"url":null,"abstract":"The integration of edge intelligence (EI) in animation design, particularly when dealing with large models, represents a significant advancement in the field of computer graphics and animation. This survey aims to provide a comprehensive overview of the current state and future prospects of EI-assisted animation design, focusing on the challenges and opportunities presented by large model implementations. Edge intelligence, characterized by its decentralized processing and real-time data analysis capabilities, offers a transformative approach to handling the computational and data-intensive demands of modern animation. This paper explores various aspects of EI in animation and then delves into the specifics of large models in animation, examining their evolution, current trends, and the inherent challenges in their implementation. Finally, the paper addresses the challenges and solutions in integrating EI with large models in animation, proposing future research directions. This survey serves as a valuable resource for researchers, animators, and technologists, offering insights into the potential of EI in revolutionizing animation design and opening new avenues for creative and efficient animation production.","PeriodicalId":501257,"journal":{"name":"Journal of Cloud Computing","volume":"51 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Edge intelligence-assisted animation design with large models: a survey\",\"authors\":\"Jing Zhu, Chuanjiang Hu, Edris Khezri, Mohd Mustafa Mohd Ghazali\",\"doi\":\"10.1186/s13677-024-00601-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The integration of edge intelligence (EI) in animation design, particularly when dealing with large models, represents a significant advancement in the field of computer graphics and animation. This survey aims to provide a comprehensive overview of the current state and future prospects of EI-assisted animation design, focusing on the challenges and opportunities presented by large model implementations. Edge intelligence, characterized by its decentralized processing and real-time data analysis capabilities, offers a transformative approach to handling the computational and data-intensive demands of modern animation. This paper explores various aspects of EI in animation and then delves into the specifics of large models in animation, examining their evolution, current trends, and the inherent challenges in their implementation. Finally, the paper addresses the challenges and solutions in integrating EI with large models in animation, proposing future research directions. This survey serves as a valuable resource for researchers, animators, and technologists, offering insights into the potential of EI in revolutionizing animation design and opening new avenues for creative and efficient animation production.\",\"PeriodicalId\":501257,\"journal\":{\"name\":\"Journal of Cloud Computing\",\"volume\":\"51 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Cloud Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1186/s13677-024-00601-3\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cloud Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s13677-024-00601-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
将边缘智能(EI)整合到动画设计中,特别是在处理大型模型时,是计算机图形学和动画领域的一大进步。本调查旨在全面概述 EI 辅助动画设计的现状和未来前景,重点关注大型模型实施所带来的挑战和机遇。边缘智能以其分散处理和实时数据分析能力为特点,为处理现代动画的计算和数据密集型需求提供了一种变革性方法。本文探讨了动画中的边缘智能的各个方面,然后深入研究了动画中大型模型的具体情况,考察了它们的演变、当前趋势以及实施过程中固有的挑战。最后,本文探讨了将动画中的电子交互与大型模型相结合所面临的挑战和解决方案,并提出了未来的研究方向。本调查报告为研究人员、动画制作人员和技术人员提供了宝贵的资源,让他们深入了解 EI 在革新动画设计方面的潜力,并为创造性和高效的动画制作开辟了新的途径。
Edge intelligence-assisted animation design with large models: a survey
The integration of edge intelligence (EI) in animation design, particularly when dealing with large models, represents a significant advancement in the field of computer graphics and animation. This survey aims to provide a comprehensive overview of the current state and future prospects of EI-assisted animation design, focusing on the challenges and opportunities presented by large model implementations. Edge intelligence, characterized by its decentralized processing and real-time data analysis capabilities, offers a transformative approach to handling the computational and data-intensive demands of modern animation. This paper explores various aspects of EI in animation and then delves into the specifics of large models in animation, examining their evolution, current trends, and the inherent challenges in their implementation. Finally, the paper addresses the challenges and solutions in integrating EI with large models in animation, proposing future research directions. This survey serves as a valuable resource for researchers, animators, and technologists, offering insights into the potential of EI in revolutionizing animation design and opening new avenues for creative and efficient animation production.