发表机构
School of Electronics and Information, Northwestern Polytechnical University; Department of Computer Science, City University of Hong Kong; School of Telecommunication Engineering, Xidian University; School of Computer Science and Engineering, Central South University; Department of Electrical Engineering, Shanghai Jiao Tong University（西北工业大学电子信息学院; 香港城市大学计算机科学系; 西安电子科技大学通信工程学院; 中南大学计算机科学与工程学院; 上海交通大学电气工程系）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究针对3D高斯点云训练效率和表示紧凑性问题，提出SPARE-GS框架，通过将结构演化公式化并动态调整基元分布，实现减少高斯数量、训练时间，提升PSNR及下游处理效率，证明全局结构预算调节的广泛适用性。
AI 中文摘要
3D高斯点云（3DGS）能实时实现高保真新视图合成，但其训练效率和表示紧凑性受过多基元扩散阻碍。为此，我们将3DGS的结构演化公式化为全局预算约束优化问题并推导最优条件。基于此提出SPARE-GS框架，它动态调整3D高斯基元分布与区域表示需求。实验表明，该框架平均减少30.38%的高斯数量和23.81%的训练时间，提升平均PSNR，还减少下游处理时间，证明全局结构预算调节的广泛适用性。
英文摘要
3D Gaussian Splatting (3DGS) achieves high-fidelity novel view synthesis in real-time; however its training efficiency and representation compactness are hindered by excessive primitive proliferation. To address this challenge, we formulate the structural evolution of 3DGS as a global budget-constrained optimization problem and derive an optimality condition, which requires the marginal utility of structural resources to be balanced across spatial regions under a finite primitive budget. Based on this formulation, we propose SPARE-GS, a general plug-and-play framework that dynamically aligns the distribution of 3D Gaussian primitives with regional representational demand. SPARE-GS estimates capacity-normalized regional demand, assigns adaptive target quotas, and uses regional budget deviations to coordinate densification, pruning and adaptive termination toward a more balanced structural allocation. Extensive experiments across standard, accelerated, and structure-enhanced 3DGS pipelines demonstrate that SPARE-GS reduces the Gaussian count and training time by an average of 30.38% and 23.81%, respectively, while improving the average PSNR. Moreover, the resulting compact representations reduce downstream processing time and improve the rate-distortion performance of diverse compression and pruning methods, demonstrating the broad applicability of global structural budget regulation.
