A Comprehensive Survey on Generative AI for Metaverse: Enabling Immersive Experience

IF 4.3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Vinay Chamola, Siva Sai, Animesh Bhargava, Ashis Sahu, Wenchao Jiang, Zehui Xiong, Dusit Niyato, Amir Hussain
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引用次数: 0

Abstract

Generative Artificial Intelligence models are Artificial Intelligence models that generate new content based on a prompt or input. The output content can be in various forms, including text, images, and video. Metaverse refers to a virtual world where users can interact with each other, objects and events in an immersive, realistic, and dynamic manner. A critical and foremost step in realizing the Metaverse is content creation for its different realms. Given Metaverse’s need for enormous content, Generative AI is a perfect technology for content creation. This paper explores how Generative AI models can help fulfil the potential of the Metaverse by assisting in the design and production of various aspects of the Metaverse and attracting users not just by creating dynamic, interactive, and personalised content at scale but also by producing various revenue-generating opportunities for users and organisations in the Metaverse. The paper analyses the Generative AI models by grouping them according to the type of content they generate, namely text, image, video, 3D visual, audio, and gaming. Various use cases in the Metaverse are explored and listed according to each type of AI Generated Content (AIGC). This paper also presents several applications and scenarios where the mixture of different Generative AI (GAI) models benefits the Metaverse. Further, this paper also enumerates the limitations and challenges of Generative AI models and the areas of future work. Despite the obstacles, Generative AI can realise the potential of the Metaverse by making it much more functional and interactive owing to the vast use cases of different types of AIGC in the Metaverse, and the age of virtual reality may not be too distant.

Abstract Image

针对 Metaverse 的生成式人工智能综合调查:实现身临其境的体验
生成式人工智能模型是根据提示或输入生成新内容的人工智能模型。输出内容可以是文本、图像和视频等各种形式。元世界(Metaverse)指的是一个虚拟世界,在这个世界里,用户可以身临其境、逼真、动态地与他人、物体和事件进行交互。实现 Metaverse 的关键和首要步骤是为其不同领域创建内容。鉴于 Metaverse 对大量内容的需求,生成式人工智能是内容创建的完美技术。本文探讨了生成式人工智能模型如何通过协助设计和制作 Metaverse 的各个方面来帮助实现 Metaverse 的潜力,以及如何不仅通过大规模创建动态、互动和个性化内容来吸引用户,而且通过为 Metaverse 中的用户和组织创造各种创收机会来吸引用户。本文根据生成内容的类型,即文本、图像、视频、三维视觉、音频和游戏,对生成式人工智能模型进行了分析。根据每种类型的人工智能生成内容(AIGC),探讨并列出了元宇宙中的各种用例。本文还介绍了几种应用和场景,在这些应用和场景中,混合使用不同的生成式人工智能(GAI)模型可为 Metaverse 带来益处。此外,本文还列举了生成式人工智能模型的局限性和挑战,以及未来的工作领域。尽管障碍重重,但由于元宇宙中不同类型 AIGC 的大量使用案例,生成式人工智能可以发挥元宇宙的潜力,使其功能性和交互性大大增强,虚拟现实时代也许并不遥远。
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来源期刊
Cognitive Computation
Cognitive Computation COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-NEUROSCIENCES
CiteScore
9.30
自引率
3.70%
发文量
116
审稿时长
>12 weeks
期刊介绍: Cognitive Computation is an international, peer-reviewed, interdisciplinary journal that publishes cutting-edge articles describing original basic and applied work involving biologically-inspired computational accounts of all aspects of natural and artificial cognitive systems. It provides a new platform for the dissemination of research, current practices and future trends in the emerging discipline of cognitive computation that bridges the gap between life sciences, social sciences, engineering, physical and mathematical sciences, and humanities.
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