Research on Intelligent 3D Modeling and Rendering and Application Analysis

This paper investigates the evolution of 3D modeling and rendering technologies, from traditional manual techniques to Artificial Intelligence (AI)-assisted processes. It explores the transition from time-intensive manual modeling to procedural and AI-based approaches, highlighting the impact of artificial intelligence in automating and enhancing the modeling process. The study also examines modern rendering engines, discussing integrating real-time performance with visual fidelity, focusing on technologies like ray tracing and AI-optimized hybrid systems. A two-part methodology is proposed: the first part analyzes various modeling platforms, including manual, procedural, and AI-based approaches, while the second part assesses rendering engines. Key tools such as Dream Fusion and Unreal Engine 5 are reviewed, identifying their technical principles and limitations. The study finds that although AI offers significant advantages in scalability and automation, it still faces challenges in controllability, precision, and hardware dependence. The paper proposes future research on AI-human collaborative frameworks and lightweight modeling systems to improve generation efficiency, reduce hardware costs, and enhance user-driven customization. This research comprehensively overviews current developments and future directions in intelligent 3D modeling and rendering technologies.