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PGSR:基于平面的高斯点云绘制,用于高效且高保真的曲面重建。

PGSR: Planar-Based Gaussian Splatting for Efficient and High-Fidelity Surface Reconstruction.

作者信息

Chen Danpeng, Li Hai, Ye Weicai, Wang Yifan, Xie Weijian, Zhai Shangjin, Wang Nan, Liu Haomin, Bao Hujun, Zhang Guofeng

出版信息

IEEE Trans Vis Comput Graph. 2025 Sep;31(9):6100-6111. doi: 10.1109/TVCG.2024.3494046.

DOI:10.1109/TVCG.2024.3494046
PMID:39509307
Abstract

Recently, 3D Gaussian Splatting (3DGS) has attracted widespread attention due to its high-quality rendering, and ultra-fast training and rendering speed. However, due to the unstructured and irregular nature of Gaussian point clouds, it is difficult to guarantee geometric reconstruction accuracy and multi-view consistency simply by relying on image reconstruction loss. Although many studies on surface reconstruction based on 3DGS have emerged recently, the quality of their meshes is generally unsatisfactory. To address this problem, we propose a fast planar-based Gaussian splatting reconstruction representation (PGSR) to achieve high-fidelity surface reconstruction while ensuring high-quality rendering. Specifically, we first introduce an unbiased depth rendering method, which directly renders the distance from the camera origin to the Gaussian plane and the corresponding normal map based on the Gaussian distribution of the point cloud, and divides the two to obtain the unbiased depth. We then introduce single-view geometric, multi-view photometric, and geometric regularization to preserve global geometric accuracy. We also propose a camera exposure compensation model to cope with scenes with large illumination variations. Experiments on indoor and outdoor scenes show that the proposed method achieves fast training and rendering while maintaining high-fidelity rendering and geometric reconstruction, outperforming 3DGS-based and NeRF-based methods.

摘要

最近,三维高斯点渲染(3DGS)因其高质量渲染以及超快的训练和渲染速度而受到广泛关注。然而,由于高斯点云的非结构化和不规则性质,仅依靠图像重建损失很难保证几何重建精度和多视图一致性。尽管最近出现了许多基于3DGS的表面重建研究,但其网格质量总体上并不理想。为了解决这个问题,我们提出了一种基于平面的快速高斯点渲染重建表示法(PGSR),以在确保高质量渲染的同时实现高保真表面重建。具体来说,我们首先引入一种无偏深度渲染方法,该方法基于点云的高斯分布直接渲染从相机原点到高斯平面的距离以及相应的法线贴图,并将两者相除得到无偏深度。然后,我们引入单视图几何、多视图光度和几何正则化来保持全局几何精度。我们还提出了一种相机曝光补偿模型来应对光照变化较大的场景。在室内和室外场景上的实验表明,该方法在保持高保真渲染和几何重建的同时实现了快速训练和渲染,优于基于3DGS和基于神经辐射场(NeRF)的方法。

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