Intelligent Metaverse Scene Content Construction

• Published in: IEEE access Vol. 11; pp. 76222 - 76241
• Main Authors: Wang, Junxiang, Chen, Siru, Liu, Yuxuan, Lau, Richen
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Agents (artificial intelligence); Artificial intelligence; Content generation; Content management; Deep learning; immersive visualization; Intelligent agents; Metaverse; Solid modeling; Surveys; Three-dimensional displays; Virtual reality; Visualization
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2023.3297873

The integration of artificial intelligence (AI) and virtual reality (VR) has revolutionized research across various scientific fields, with AI-driven VR simulations finding applications in education, healthcare, and entertainment. However, existing literature lacks a comprehensive investigation that systematically summarizes the fundamental characteristics and development trajectory of AI-generated visual content in the metaverse. This survey focuses on intelligent metaverse scene content construction, aiming to address this gap by exploring the application of AI in content generation. It investigates scene content generation, simulation biology, personalized content, and intelligent agents. Analyzing the current state and identifying common features, this survey provides a detailed description of methods for constructing intelligent metaverse scenes. The primary contribution is a comprehensive analysis of the current landscape of intelligent visual content production in the metaverse, highlighting emerging trends. The discussion on methods for constructing intelligent scene content in the metaverse suggests that in the era of intelligence, it has the potential to become the dominant approach for content creation in metaverse scenes.