3D Gaussian Splatting (3DGS) has emerged as an advanced technique for real-time novel view synthesis by representing scene geometry and appearance using differentiable Gaussian primitives. However, efficiently computing precise Gaussian-tile intersections remains a critical task in the rasterization pipeline. To this end, we propose QuadBox, a method that leverages four axis-aligned bounding boxes to tightly encapsulate projected Gaussians in a discrete manner. First, we derive a geometry-aware stretching factor that enables the construction of a tile-aligned QuadBox, which covers the elliptical projection and largely excludes irrelevant tiles. Second, we introduce QPass, a single-pass tile traversal algorithm that exhaustively exploits the discrete nature of QuadBox, ensuring that the tile intersection check is performed with simple interval tests. Experiments on public datasets show that our method accelerates the rendering speed of 3DGS by 1.85$\times$. Code is available at \href{https://github.com/Powertony102/QuadBox}{https://github.com/Powertony102/QuadBox}.

翻译：三维高斯点云（3DGS）通过使用可微高斯体元表示场景几何与外观，已成为一种用于实时新视角合成的先进技术。然而，在光栅化管线中高效计算精确的高斯-瓦片交叉仍是一项关键任务。为此，我们提出QuadBox方法，利用四个轴对齐包围盒以离散方式紧密包裹高斯投影。首先，推导出几何感知的拉伸因子，用于构建与瓦片对齐的QuadBox，该包围盒能够覆盖椭圆投影并排除大量无关瓦片。其次，引入单次遍历瓦片算法QPass，该算法充分利用QuadBox的离散特性，仅通过简单区间测试即可完成瓦片交叉检测。在公开数据集上的实验表明，本方法将3DGS的渲染速度提升1.85倍。代码已发布于\href{https://github.com/Powertony102/QuadBox}{https://github.com/Powertony102/QuadBox}。