Octree-GS: Towards Consistent Real-time Rendering with LOD-Structured 3D
  Gaussians
Kerui Ren Lihan Jiang Tao Lu Mulin Yu Linning Xu Zhangkai Ni Bo Dai
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.