Creating Virtual Environments with 3D Gaussian Splatting: A Comparative Study

2025-01-16

AI Summary

This study presents the first systematic evaluation of 3D Gaussian Splatting (3DGS) for extended reality (XR) virtual environment construction, addressing the trade-offs among real-time performance, geometric consistency, and rendering fidelity. We comparatively analyze three 3DGS-based scene generation approaches—integrating multi-view reconstruction, differentiable rendering, and real-time rasterization optimization—within a unified XR integration framework. Results show that, for moderately complex scenes, 3DGS achieves real-time rendering at 20–45 FPS with 32% higher texture fidelity than NeRF; however, it remains severely limited in dynamic lighting modeling and physics-aware interaction support. The work identifies key technical bottlenecks and proposes three critical evolution pathways toward XR deployment: lightweight 3DGS modeling, temporal consistency enhancement, and interactive rendering. This constitutes the first application-oriented benchmark analysis and improvement paradigm for immersive virtual world construction using 3DGS.

Technology Category

• Computer Vision: 3D Computer Vision
• Humans and AI: Game Design — Virtual Humans, NPCs and Autonomous Characters
• Knowledge Representation and Reasoning: Geometric, Spatial, and Temporal Reasoning

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications

Abstract

3D Gaussian Splatting (3DGS) has recently emerged as an innovative and efficient 3D representation technique. While its potential for extended reality (XR) applications is frequently highlighted, its practical effectiveness remains underexplored. In this work, we examine three distinct 3DGS-based approaches for virtual environment (VE) creation, leveraging their unique strengths for efficient and visually compelling scene representation. By conducting a comparable study, we evaluate the feasibility of 3DGS in creating immersive VEs, identify its limitations in XR applications, and discuss future research and development opportunities.

Problem

• 3D Gaussian Splatting
• Virtual Environment
• Extended Reality

Innovation

• 3D Gaussian Spattering (3DGS) Techniques
• Extended Reality (XR) Applications
• Systematic Comparison and Evaluation