3D Gaussian Splatting (3DGS) excels in novel view synthesis, balancing advanced rendering quality with real-time performance. However, in trained scenes, a large number of Gaussians with low opacity significantly increase rendering costs. This issue arises due to flaws in the split and clone operations during the densification process, which lead to extensive Gaussian overlap and subsequent opacity reduction. To enhance the efficiency of Gaussian utilization, we improve the adaptive density control of 3DGS. First, we introduce a more efficient long-axis split operation to replace the original clone and split, which mitigates Gaussian overlap and improves densification efficiency. Second, we propose a simple adaptive pruning technique to reduce the number of low-opacity Gaussians. Finally, by dynamically lowering the splitting threshold and applying importance weighting, the efficiency of Gaussian utilization is further improved. We evaluate our proposed method on various challenging real-world datasets. Experimental results show that our Efficient Density Control (EDC) can enhance both the rendering speed and quality.
3D Gaussian Splatting (3DGS) 在新视角合成中表现出色，兼顾了先进的渲染质量和实时性能。然而，在已训练场景中，大量低不透明度的高斯点显著增加了渲染成本。此问题主要源于致密化过程中分裂与克隆操作的缺陷，这导致高斯点的严重重叠及随之而来的不透明度降低。 为提高高斯点的利用效率，我们改进了3DGS的自适应密度控制方法。首先，我们引入了一种更高效的长轴分裂操作，替代原有的克隆与分裂机制，从而减少高斯重叠并提升致密化效率。其次，我们提出了一种简单的自适应剪枝技术，用以减少低不透明度高斯点的数量。最后，通过动态降低分裂阈值并引入重要性加权策略，进一步优化了高斯点的利用效率。 我们在多个具有挑战性的真实场景数据集上对该方法进行了评估。实验结果表明，所提出的高效密度控制方法（Efficient Density Control, EDC）能够同时提升渲染速度和质量。