Sort-free Gaussian Splatting via Weighted Sum Rendering
Qiqi Hou, Randall Rauwendaal, Zifeng Li, Hoang Le, Farzad Farhadzadeh, Fatih Porikli, Alexei Bourd, Amir Said
摘要
Recently, 3D Gaussian Splatting (3DGS) has emerged as a significant advancement in 3D scene reconstruction, attracting considerable attention due to its ability to recover high-fidelity details while maintaining low complexity. Despite the promising results achieved by 3DGS, its rendering performance is constrained by its dependence on costly non-commutative alpha-blending operations. These operations mandate complex view dependent sorting operations that introduce computational overhead, especially on the resource-constrained platforms such as mobile phones. In this paper, we propose Weighted Sum Rendering, which approximates alpha blending with weighted sums, thereby removing the need for sorting. This simplifies implementation, delivers superior performance, and eliminates the ``popping'' artifacts caused by sorting. Experimental results show that optimizing a generalized Gaussian splatting formulation to the new differentiable rendering yields competitive image quality. The method was implemented and tested in a mobile device GPU, achieving on average faster rendering.
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引用它的顶会 Paper12
- Faster-GS: Analyzing and Improving Gaussian Splatting OptimizationFlorian Hahlbohm, Linus Franke, Martin Eisemann, Marcus A. MagnorCVPR 2026 · 被引用 16 次
- Mobile-GS: Real-time Gaussian Splatting for Mobile DevicesXiaobiao Du, Yida Wang, Kun Zhan, Xin YuICLR 2026 · 被引用 13 次
- 3DGEER: 3D Gaussian Rendering Made Exact and Efficient for Generic CamerasZixun Huang, Cho-Ying Wu, Yuliang Guo, Xinyu Huang 等ICLR 2026 · 被引用 9 次
- StochasticSplats: Stochastic Rasterization for Sorting-Free 3D Gaussian SplattingShakiba Kheradmand, Delio Vicini, George Kopanas, Dmitry Lagun 等ICCV 2025 · 被引用 7 次
- Depth Peeling for High-Fidelity Gaussian-Enhanced Surfel RenderingKeyang Ye, Hongzhi Wu, Kun ZhouCVPR 2026 · 被引用 2 次
它引用的顶会 Paper22
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