EfficientGS: Streamlining Gaussian Splatting for Large-Scale High-Resolution Scene Representation

Wenkai Liu, Tao Guan, Bin Zhu, Luoyuan Xu, Zikai Song, Dan Li, Yuesong Wang, Wei Yang

Abstract: Three-dimensional Gaussian splatting (3DGS) has become a pivotal technology for 3-D scene representation. However, its application to large-scale, high-resolution scenes (exceeding 4k × 4k pixels) is hindered by the excessive computational and storage requirements for managing a large number of Gaussians. To address these challenges, we propose “EfficientGS,” an advanced approach that optimizes 3DGS for high-resolution, large-scale scenes. First, we design a more selective densification to reduce the overproliferation of Gaussians. Second, we develop a pruning mechanism to remove redundant Gaussians that only serve as auxiliaries to adjacent ones. Finally, we introduce a sparse order increment strategy for spherical harmonics to reduce unnecessary storage. Our empirical evaluations on various datasets, including extensive 4 K+ aerial images, demonstrate that EfficientGS can achieve high rendering fidelity with less computational and storage cost. Our code is available at https://github.com/wenkaier/EfficientGS.

External IDs:dblp:journals/ieeemm/LiuGZXSLWY25