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.
我们提出了群体众包点云投影（Crowd-Sourced Splatting, CSS），这是一种新颖的3D高斯投影（3D Gaussian Splatting, 3DGS）管线，旨在解决使用群体众包图像进行无姿态场景重建的挑战。重建历史上重要但无法直接接触的场景一直是研究人员的梦想。然而，传统的3D技术在缺失相机姿态、视角受限和光照不一致的情况下表现不佳。CSS通过稳健的几何先验和先进的光照建模，成功应对这些挑战，从而在复杂的真实世界条件下实现高质量的新视角合成。我们的方法相比现有方法表现出明显的改进，为增强现实、虚拟现实以及大规模3D重建中的更准确和灵活的应用铺平了道路。