用圆柱三平面表示法提升全景图像的新视角合成效果。
CylinderSplat: 3D Gaussian Splatting with Cylindrical Triplanes for Panoramic Novel View Synthesis
- 提出圆柱三平面结构，更贴合全景数据的几何特性。
- 单图到多图输入皆可处理，重建质量与几何精度领先现有方法。
- 适合需要高精度全景生成的视觉应用，如虚拟现实、数字孪生。
前馈式3D高斯点阵（3DGS）在实时新视角合成中表现优异，但应用于全景图像仍具挑战。现有方法依赖多视角代价体进行几何优化，在稀疏视图下难以解决遮挡问题。标准体素表示如笛卡尔三平面在捕捉360°场景固有结构时表现不佳，导致畸变和混叠。本文提出CylinderSplat，一种面向全景3DGS的前馈框架，核心是新型圆柱三平面表示，更契合全景数据与曼哈顿世界假设下的真实结构。采用双分支架构：基于像素的分支重建可观测区域，基于体积的分支利用圆柱三平面补全遮挡或稀疏观测区域。框架支持从单张到多张全景图的灵活输入。大量实验表明，CylinderSplat在单视图与多视图全景新视角合成上均达到当前最优，显著优于已有方法的重建质量与几何准确性。
原文摘要 · Abstract (English)
Feed-forward 3D Gaussian Splatting (3DGS) has shown great promise for real-time novel view synthesis, but its application to panoramic imagery remains challenging. Existing methods often rely on multi-view cost volumes for geometric refinement, which struggle to resolve occlusions in sparse-view scenarios. Furthermore, standard volumetric representations like Cartesian Triplanes are poor in capturing the inherent geometry of $360^\circ$ scenes, leading to distortion and aliasing. In this work, we introduce CylinderSplat, a feed-forward framework for panoramic 3DGS that addresses these limitations. The core of our method is a new {cylindrical Triplane} representation, which is better aligned with panoramic data and real-world structures adhering to the Manhattan-world assumption. We use a dual-branch architecture: a pixel-based branch reconstructs well-observed regions, while a volume-based branch leverages the cylindrical Triplane to complete occluded or sparsely-viewed areas. Our framework is designed to flexibly handle a variable number of input views, from single to multiple panoramas. Extensive experiments demonstrate that CylinderSplat achieves state-of-the-art results in both single-view and multi-view panoramic novel view synthesis, outperforming previous methods in both reconstruction quality and geometric accuracy.
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