让3D高斯点纹理自适应调整，更省内存还更清晰。
A$^2$TG: Adaptive Anisotropic Textured Gaussians for Efficient 3D Scene Representation
- 每个高斯点用可变形状纹理，按需分配细节
- 内存占用降低，画质与固定纹理方法相当
- 适合追求高效渲染的3D重建和可视化应用
高斯点阵已成为高质量、实时3D场景渲染的强大表示方法。尽管近期工作通过引入可学习纹理丰富视觉表现，但现有方法为每个基元分配固定方形纹理，导致内存使用效率低且难以适应场景变化。本文提出自适应各向异性纹理高斯（A²TG），通过为每个基元配备各向异性纹理，实现对纹理分辨率和长宽比的联合自适应调节。该方法基于梯度引导的自适应规则，实现非均匀、感知细节的纹理分配，更好地匹配高斯点阵的各向异性特性。实验表明，A²TG在多个基准数据集上均优于固定纹理高斯点阵方法，在保持相近渲染保真度的同时显著降低内存需求。
原文摘要 · Abstract (English)
Gaussian Splatting has emerged as a powerful representation for high-quality, real-time 3D scene rendering. While recent works extend Gaussians with learnable textures to enrich visual appearance, existing approaches allocate a fixed square texture per primitive, leading to inefficient memory usage and limited adaptability to scene variability. In this paper, we introduce adaptive anisotropic textured Gaussians (A$^2$TG), a novel representation that generalizes textured Gaussians by equipping each primitive with an anisotropic texture. Our method employs a gradient-guided adaptive rule to jointly determine texture resolution and aspect ratio, enabling non-uniform, detail-aware allocation that aligns with the anisotropic nature of Gaussian splats. This design significantly improves texture efficiency, reducing memory consumption while enhancing image quality. Experiments on multiple benchmark datasets demonstrate that A TG consistently outperforms fixed-texture Gaussian Splatting methods, achieving comparable rendering fidelity with substantially lower memory requirements. Project page: http://github.com/Rickyeeeeee/A2TG.
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