LiteTex-GS: Fast and Lightweight Texturing for Gaussian Splatting

2026-09-20

AI Summary

为解决高斯点云渲染中细节纹理与计算效率之间的矛盾，提出了一种快速轻量级的纹理框架LiteTex-GS，通过自适应分配分辨率和优化更新规则来提高效率。

Abstract

Gaussian Splatting has enabled real-time novel view synthesis, but its tightly coupled geometry and appearance representation often require a large number of primitives to reproduce high-frequency texture details, leading to substantial memory and optimization costs. Recent textured 2D Gaussian methods alleviate this limitation by attaching texture maps to Gaussian primitives. However, bridging the fundamental structural gap between discrete Gaussians and continuous 2D grids requires complex parameterizations that introduce severe computational overhead. This overhead fundamentally compromises the original efficiency of Gaussian Splatting, making the balance between detailed texturing and computational agility an unresolved challenge. To address these challenges, we propose LiteTex-GS, a fast and lightweight texturing framework for Gaussian Splatting. Our method initializes an extremely compact representation, assigning minimal local texture to each Gaussian and progressively allocates higher resolution only to primitives with significant reconstruction errors. To maintain a streamlined geometric scaffold, we introduce a contribution- and area-aware pruning strategy that eliminates low-utility Gaussians. Furthermore, to mitigate the gradient dilution caused by texture upsampling, we design a resolution-aware update rule that preserves rapid and stable convergence. Extensive experiments on standard novel view synthesis benchmarks demonstrate that our method achieves competitive or superior rendering quality while using substantially fewer parameters and less training time than existing textured Gaussian baselines.

Problem

• Gaussian Splatting
• texturing
• computational overhead
• real-time novel view synthesis
• memory and optimization costs

Innovation

• Gaussian Splatting
• Texture Mapping
• Resolution-aware Update
• Contribution- and Area-aware Pruning
• Lightweight Texturing