Octree-GS: Towards Consistent Real-time Rendering with LOD-Structured 3D Gaussians

Fuente: arXiv
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Main Authors: Ren, Kerui, Jiang, Lihan, Lu, Tao, Yu, Mulin, Xu, Linning, Ni, Zhangkai, Dai, Bo
Format: Preprint
Published: 2024
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author Ren, Kerui
Jiang, Lihan
Lu, Tao
Yu, Mulin
Xu, Linning
Ni, Zhangkai
Dai, Bo
author_facet Ren, Kerui
Jiang, Lihan
Lu, Tao
Yu, Mulin
Xu, Linning
Ni, Zhangkai
Dai, Bo
contents The recent 3D Gaussian splatting (3D-GS) has shown remarkable rendering fidelity and efficiency compared to NeRF-based neural scene representations. While demonstrating the potential for real-time rendering, 3D-GS encounters rendering bottlenecks in large scenes with complex details due to an excessive number of Gaussian primitives located within the viewing frustum. This limitation is particularly noticeable in zoom-out views and can lead to inconsistent rendering speeds in scenes with varying details. Moreover, it often struggles to capture the corresponding level of details at different scales with its heuristic density control operation. Inspired by the Level-of-Detail (LOD) techniques, we introduce Octree-GS, featuring an LOD-structured 3D Gaussian approach supporting level-of-detail decomposition for scene representation that contributes to the final rendering results. Our model dynamically selects the appropriate level from the set of multi-resolution anchor points, ensuring consistent rendering performance with adaptive LOD adjustments while maintaining high-fidelity rendering results.
format Preprint
id arxiv_https___arxiv_org_abs_2403_17898
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Octree-GS: Towards Consistent Real-time Rendering with LOD-Structured 3D Gaussians
Ren, Kerui
Jiang, Lihan
Lu, Tao
Yu, Mulin
Xu, Linning
Ni, Zhangkai
Dai, Bo
Computer Vision and Pattern Recognition
The recent 3D Gaussian splatting (3D-GS) has shown remarkable rendering fidelity and efficiency compared to NeRF-based neural scene representations. While demonstrating the potential for real-time rendering, 3D-GS encounters rendering bottlenecks in large scenes with complex details due to an excessive number of Gaussian primitives located within the viewing frustum. This limitation is particularly noticeable in zoom-out views and can lead to inconsistent rendering speeds in scenes with varying details. Moreover, it often struggles to capture the corresponding level of details at different scales with its heuristic density control operation. Inspired by the Level-of-Detail (LOD) techniques, we introduce Octree-GS, featuring an LOD-structured 3D Gaussian approach supporting level-of-detail decomposition for scene representation that contributes to the final rendering results. Our model dynamically selects the appropriate level from the set of multi-resolution anchor points, ensuring consistent rendering performance with adaptive LOD adjustments while maintaining high-fidelity rendering results.
title Octree-GS: Towards Consistent Real-time Rendering with LOD-Structured 3D Gaussians
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2403.17898