快速重建动态点云与高斯斑点，支持真实场景下多相机部署。
A Fast Volumetric Capture and Reconstruction Pipeline for Dynamic Point Clouds and Gaussian Splats
- 基于RGB-D或RGB输入，实时生成点云与高斯斑点3D表示
- 在5-10帧/秒下实现现场预览，支持任意相机布局和光照条件
- 开源框架，适用于野外部署与可视化插件集成
我们提出一个高效快速的体素捕获与重建系统，可处理RGB-D或仅RGB输入，生成点云和高斯斑点形式的3D表示。针对高斯斑点重建，改进了GPS-Gaussian回归器，在极低开销下实现高质量重建。系统设计便于部署，支持不受控光照、任意背景及灵活相机配置（包括稀疏设置、任意相机数量与基线）。捕获数据可导出为PLY、MPEG V-PCC和SPLAT等标准格式，并通过基于网页的查看器或Unity/Unreal插件进行可视化。系统提供5-10帧/秒的现场实时预览，涵盖输入与重建结果。本文展示部署性分析与针对性消融实验。完整框架开源，促进复现与后续研究。
原文摘要 · Abstract (English)
We present a fast and efficient volumetric capture and reconstruction system that processes either RGB-D or RGB-only input to generate 3D representations in the form of point clouds and Gaussian splats. For Gaussian splat reconstructions, we took the GPS-Gaussian regressor and improved it, enabling high-quality reconstructions with minimal overhead. The system is designed for easy setup and deployment, supporting in-the-wild operation under uncontrolled illumination and arbitrary backgrounds, as well as flexible camera configurations, including sparse setups, arbitrary camera numbers and baselines. Captured data can be exported in standard formats such as PLY, MPEG V-PCC, and SPLAT, and visualized through a web-based viewer or Unity/Unreal plugins. A live on-location preview of both input and reconstruction is available at 5-10 FPS. We present qualitative findings focused on deployability and targeted ablations. The complete framework is open-source, facilitating reproducibility and further research.
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