TNT-GS: Truncated and Tailored Gaussian Splatting

摘要

Gaussian Splatting (GS) is widely used for efficient 3D scene representation and rendering by modeling scenes as continuous Gaussian distributions. However, GS struggles with high-frequency details and sharp transitions due to its low-pass filtering effect, often requiring multiple Gaussian stacking, which increases computational and memory costs. To overcome these limitations, we propose Truncated and Tailored Gaussian Splatting (TNT-GS), a novel approach that enhances shape complexity and preserves sharp boundaries. Our method truncates Gaussians to generate sharp edges and flexible shapes without excessive stacking, improving efficiency. We also introduce learnable parameters to dynamically tailor the receptive field of the primitives, optimizing the balance between high-frequency details and smooth regions. Furthermore, we employ specialized densification strategies to further improve efficiency during tile computation. Experimental results show that TNT-GS outperforms state-of-the-art methods in storage efficiency and rendering speed, offering a robust solution for real-time rendering. The code of TNT-GS is available at https://github.com/GoogolplexGoodenough/TNT-GS.