BlockGaussian：基于自适应分块高斯溅射的高效大规模场景新视角合成

BlockGaussian: Efficient Large-Scale Scene Novel View Synthesis via Adaptive Block-Based Gaussian Splatting

April 12, 2025

作者: Yongchang Wu, Zipeng Qi, Zhenwei Shi, Zhengxia Zou

cs.AI

摘要

近期，3D高斯溅射（3DGS）技术的突破在新视角合成任务中展现了显著潜力。尽管分而治之的策略已实现大规模场景重建，但在场景划分、优化与合并过程中仍面临重大挑战。本文提出BlockGaussian，一种创新框架，通过引入内容感知的场景分割策略与可见性感知的区块优化，实现了高效且高质量的大规模场景重建。具体而言，我们的方法考量了不同区域间的内容复杂度差异，在场景划分时平衡计算负载，从而提升重建效率。针对独立区块优化中的监督失配问题，我们在单个区块优化过程中引入辅助点，以对齐真实监督，进而提升重建质量。此外，我们提出了一种伪视图几何约束，有效缓解了区块合并时因空中漂浮物导致的渲染退化问题。在大规模场景上的广泛实验表明，我们的方法在重建效率与渲染质量上均达到了业界领先水平，优化速度提升5倍，并在多个基准测试中平均PSNR提高了1.21 dB。尤为值得一提的是，BlockGaussian大幅降低了计算需求，使得在单块24GB显存设备上完成大规模场景重建成为可能。项目页面详见https://github.com/SunshineWYC/BlockGaussian。

English

The recent advancements in 3D Gaussian Splatting (3DGS) have demonstrated remarkable potential in novel view synthesis tasks. The divide-and-conquer paradigm has enabled large-scale scene reconstruction, but significant challenges remain in scene partitioning, optimization, and merging processes. This paper introduces BlockGaussian, a novel framework incorporating a content-aware scene partition strategy and visibility-aware block optimization to achieve efficient and high-quality large-scale scene reconstruction. Specifically, our approach considers the content-complexity variation across different regions and balances computational load during scene partitioning, enabling efficient scene reconstruction. To tackle the supervision mismatch issue during independent block optimization, we introduce auxiliary points during individual block optimization to align the ground-truth supervision, which enhances the reconstruction quality. Furthermore, we propose a pseudo-view geometry constraint that effectively mitigates rendering degradation caused by airspace floaters during block merging. Extensive experiments on large-scale scenes demonstrate that our approach achieves state-of-the-art performance in both reconstruction efficiency and rendering quality, with a 5x speedup in optimization and an average PSNR improvement of 1.21 dB on multiple benchmarks. Notably, BlockGaussian significantly reduces computational requirements, enabling large-scale scene reconstruction on a single 24GB VRAM device. The project page is available at https://github.com/SunshineWYC/BlockGaussian