BlockGaussian：基於自適應塊狀高斯潑濺的高效大規模場景新視角合成

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）技術的進展在新視角合成任務中展現了顯著潛力。分而治之的範式雖已實現大規模場景重建，但在場景分割、優化與合併過程中仍面臨重大挑戰。本文提出BlockGaussian，這是一個創新框架，融合了內容感知的場景分割策略與可見性感知的區塊優化，旨在實現高效且高質量的大規模場景重建。具體而言，我們的方法考慮了不同區域間內容複雜度的變化，並在場景分割時平衡計算負載，從而提升場景重建效率。為解決獨立區塊優化過程中的監督不匹配問題，我們在個別區塊優化時引入輔助點，以對齊真實監督，從而提升重建質量。此外，我們提出了一種偽視圖幾何約束，有效緩解了區塊合併時因空域漂浮物導致的渲染退化問題。在大規模場景上的廣泛實驗表明，我們的方法在重建效率與渲染質量上均達到了業界領先水平，優化速度提升了5倍，並在多個基準測試中平均PSNR提升了1.21 dB。值得注意的是，BlockGaussian顯著降低了計算需求，使得在單一24GB顯存設備上進行大規模場景重建成為可能。項目頁面請訪問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