SPARE-GS: Structural Parsimony and Resource Efficiency for 3D Gaussian Splatting

• URL: http://arxiv.org/abs/2607.16624v1
• Date: Sat, 18 Jul 2026 03:55:12 GMT
• Title: SPARE-GS: Structural Parsimony and Resource Efficiency for 3D Gaussian Splatting
• Abstract summary: 3D Gaussian Splatting (3DGS) achieves high-fidelity novel view synthesis in real-time.<n>But its training efficiency and representation compactness are hindered by excessive primitive proliferation.<n>We propose SPARE-GS, a framework that dynamically aligns the distribution of 3D Gaussian primitives with regional representational demand.
• Score: 70.5411715784827
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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