SparseOIT：通过主动集方法改进顺序无关透明 3DGS
SparseOIT: Improving Order-Independent Transparency 3DGS via Active Set Method
将主动集方法引入 OIT 3DGS 渲染方程求解，利用高斯泼溅间稀疏依赖加速重建，为透明/非朗伯材质的新视角合成提供可复用优化框架。
原文依据 we propose SparseOIT, an OIT-based 3DGS reconstruction algorithm that maintains an active set of gaussian splats
摘要译文
由模型翻译 · 术语统一 · 请对照原文核对关键结论3D 高斯泼溅（3DGS）在过去几年中因其照片级的视觉外观而广受欢迎。然而，3DGS 使用的体渲染不适合非朗伯或透明材质的物体。为解决这一问题，一类顺序无关透明（OIT）渲染方法提出移除或修改 3DGS 渲染方程中的深度排序步骤。然而，基于 OIT 的方法的潜力仍未得到充分探索。本文观察到，OIT 对渲染方程的修改显著降低了个体高斯泼溅之间的相互独立性，导致非常稀疏的变量依赖关系，这种依赖关系可以被主动集方法等特定优化技术所利用。为此，我们提出 SparseOIT，一种基于 OIT 的 3DGS 重建算法，它维护一个高斯泼溅的主动集，并享有与潜在稀疏性成正比的加速比。SparseOIT 的设计联合考虑了 OIT 渲染方程、重建算法和几何正则化。通过大量实验，我们证明 SparseOIT 大幅优于 OIT 系列中的现有方法，并且与基于体渲染的最优 3DGS 重建方法相比也达到了可比的性能。
英文原文摘要 1372 字符
3D Gaussian Splatting (3DGS) has received tremendous popularity over the past few years due to its photorealistic visual appearance. However, 3DGS uses volumetric rendering that is not suitable for objects with non-lambertian or transparent materials. To remedy this issue, a family of Order-Independent Transparency (OIT) rendering methods propose to remove or modify the depth sorting step in the 3DGS rendering equation. However, the potential of OIT-based method is still underexplored. In this paper, we observe that the OIT modifications to the rendering equation significantly reduce the inter-independence among individual gaussian splats, resulting in very sparse variable dependencies that can be harnessed by specific optimization techniques such as active set method. To this end, we propose SparseOIT, an OIT-based 3DGS reconstruction algorithm that maintains an active set of gaussian splats and enjoys an acceleration ratio that is proportional to the potential sparsity. SparseOIT is designed by jointly considering the OIT rendering equation, the reconstruction algorithm and the geometric regularization. Through extensive experiments, we demonstrate that SparseOIT outperforms existing methods in the OIT-family by a large margin and also achieves comparable performance to the state-of-the-art 3DGS reconstruction methods based on volumetric rendering.