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.

翻译：高斯泼溅已成为实现高质量、实时三维场景渲染的强大表示方法。尽管近期研究通过引入可学习纹理来扩展高斯模型以丰富视觉外观，但现有方法为每个图元分配固定的方形纹理，导致内存使用效率低下且对场景变化的适应性有限。本文提出自适应各向异性纹理高斯模型（A$^2$TG），这是一种通过为每个图元配备各向异性纹理来推广纹理高斯模型的新型表示方法。我们的方法采用梯度引导的自适应规则联合确定纹理分辨率和纵横比，实现与高斯泼溅各向异性特性对齐的非均匀、细节感知分配。该设计显著提高了纹理效率，在降低内存消耗的同时提升了图像质量。在多个基准数据集上的实验表明，A$^2$TG始终优于固定纹理的高斯泼溅方法，在显著降低内存需求的同时实现了可比的渲染保真度。