CVGRHCDec 9, 2024

Advancing Extended Reality with 3D Gaussian Splatting: Innovations and Prospects

arXiv:2412.06257v226 citationsh-index: 132025 IEEE International Conference on Artificial Intelligence and eXtended and Virtual Reality (AIxVR)
Originality Synthesis-oriented
AI Analysis

It addresses the underexplored application of 3DGS to XR, providing a roadmap for researchers and developers in the XR field, but it is incremental as it focuses on synthesis and review rather than new experimental results.

This paper synthesizes innovations in 3D Gaussian Splatting (3DGS) to advance Extended Reality (XR) by reviewing existing research, analyzing XR-relevant innovations, and proposing a taxonomy and future research areas.

3D Gaussian Splatting (3DGS) has attracted significant attention for its potential to revolutionize 3D representation, rendering, and interaction. Despite the rapid growth of 3DGS research, its direct application to Extended Reality (XR) remains underexplored. Although many studies recognize the potential of 3DGS for XR, few have explicitly focused on or demonstrated its effectiveness within XR environments. In this paper, we aim to synthesize innovations in 3DGS that show specific potential for advancing XR research and development. We conduct a comprehensive review of publicly available 3DGS papers, with a focus on those referencing XR-related concepts. Additionally, we perform an in-depth analysis of innovations explicitly relevant to XR and propose a taxonomy to highlight their significance. Building on these insights, we propose several prospective XR research areas where 3DGS can make promising contributions, yet remain rarely touched. By investigating the intersection of 3DGS and XR, this paper provides a roadmap to push the boundaries of XR using cutting-edge 3DGS techniques.

Foundations

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