用众包照片重建无相机位姿的3D场景，实现高质量新视角合成。
CSS: Overcoming Pose and Scene Challenges in Crowd-Sourced 3D Gaussian Splatting
- 基于几何先验与光照建模，解决无位姿图像的3D重建难题。
- 在真实复杂场景下实现清晰的新视角生成，优于现有方法。
- 适合缺乏专业拍摄数据的AR/VR及大规模3D重建应用。
我们提出众包点云渲染（CSS），一种新型3D高斯点阵（3DGS）流程，旨在利用众包图像克服无相机位姿场景重建的挑战。长期以来，从历史场景的公众照片中重建3D画面是研究者的梦想。但传统3D技术在缺失相机位姿、视角受限和光照不一致等问题面前表现不佳。CSS通过鲁棒的几何先验与先进的光照建模，实现了在复杂真实条件下高质量的新视角合成。实验表明，该方法在多个真实数据集上显著优于现有方案，为AR、VR及大规模3D重建提供了更精准灵活的技术路径。
原文摘要 · Abstract (English)
We introduce Crowd-Sourced Splatting (CSS), a novel 3D Gaussian Splatting (3DGS) pipeline designed to overcome the challenges of pose-free scene reconstruction using crowd-sourced imagery. The dream of reconstructing historically significant but inaccessible scenes from collections of photographs has long captivated researchers. However, traditional 3D techniques struggle with missing camera poses, limited viewpoints, and inconsistent lighting. CSS addresses these challenges through robust geometric priors and advanced illumination modeling, enabling high-quality novel view synthesis under complex, real-world conditions. Our method demonstrates clear improvements over existing approaches, paving the way for more accurate and flexible applications in AR, VR, and large-scale 3D reconstruction.
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