3D Gaussian Splatting (3DGS) excels at producing highly detailed 3D reconstructions, but these scenes often require specialised renderers for effective visualisation. In contrast, point clouds are a widely used 3D representation and are compatible with most popular 3D processing software, yet converting 3DGS scenes into point clouds is a complex challenge. In this work we introduce 3DGS-to-PC, a flexible and highly customisable framework that is capable of transforming 3DGS scenes into dense, high-accuracy point clouds. We sample points probabilistically from each Gaussian as a 3D density function. We additionally threshold new points using the Mahalanobis distance to the Gaussian centre, preventing extreme outliers. The result is a point cloud that closely represents the shape encoded into the 3D Gaussian scene. Individual Gaussians use spherical harmonics to adapt colours depending on view, and each point may contribute only subtle colour hints to the resulting rendered scene. To avoid spurious or incorrect colours that do not fit with the final point cloud, we recalculate Gaussian colours via a customised image rendering approach, assigning each Gaussian the colour of the pixel to which it contributes most across all views. 3DGS-to-PC also supports mesh generation through Poisson Surface Reconstruction, applied to points sampled from predicted surface Gaussians. This allows coloured meshes to be generated from 3DGS scenes without the need for re-training. This package is highly customisable and capability of simple integration into existing 3DGS pipelines. 3DGS-to-PC provides a powerful tool for converting 3DGS data into point cloud and surface-based formats.
三维高斯散点（3D Gaussian Splatting, 3DGS）在生成高度细节化的三维重建方面表现出色，但这些场景通常需要专用渲染器进行有效的可视化。相比之下，点云是一种广泛使用的三维表示形式，与大多数流行的三维处理软件兼容，但将 3DGS 场景转换为点云是一个复杂的挑战。 在本研究中，我们提出了 3DGS-to-PC，一个灵活且高度可定制的框架，能够将 3DGS 场景转换为密集且高精度的点云。我们将每个高斯看作三维密度函数，以概率方式采样点。此外，我们通过马氏距离（Mahalanobis Distance）对新生成的点进行阈值筛选，从而避免极端离群值的影响。最终生成的点云能够紧密表示 3DGS 场景中编码的形状。 在颜色处理上，单个高斯使用球谐函数根据视角自适应颜色，每个点仅对渲染场景提供细微的颜色提示。为避免与最终点云不匹配的虚假或错误颜色，我们通过定制的图像渲染方法重新计算高斯颜色，为每个高斯分配其在所有视角中对某像素贡献最大的颜色。 3DGS-to-PC 还支持通过泊松表面重建（Poisson Surface Reconstruction）生成网格，应用于从预测的表面高斯采样的点。这使得可以从 3DGS 场景生成彩色网格，而无需重新训练。 此工具包高度可定制，并可轻松集成到现有的 3DGS 流程中。3DGS-to-PC 提供了一种强大的工具，用于将 3DGS 数据转换为基于点云和表面的格式。