Gaussian Splatting has recently emerged as the go-to representation for reconstructing and rendering 3D scenes. The transition from 3D to 2D Gaussian primitives has further improved multi-view consistency and surface reconstruction accuracy. In this work we highlight the similarity between 2D Gaussian Splatting (2DGS) and billboards from traditional computer graphics. Both use flat semi-transparent 2D geometry that is positioned, oriented and scaled in 3D space. However 2DGS uses a solid color per splat and an opacity modulated by a Gaussian distribution, where billboards are more expressive, modulating the color with a uv-parameterized texture. We propose to unify these concepts by presenting Gaussian Billboards, a modification of 2DGS to add spatially-varying color achieved using per-splat texture interpolation. The result is a mixture of the two representations, which benefits from both the robust scene optimization power of 2DGS and the expressiveness of texture mapping. We show that our method can improve the sharpness and quality of the scene representation in a wide range of qualitative and quantitative evaluations compared to the original 2DGS implementation.

翻译：高斯泼溅技术近期已成为三维场景重建与渲染的首选表征方法。从三维到二维高斯基元的转变进一步提升了多视角一致性与表面重建精度。本研究重点探讨了二维高斯泼溅与传统计算机图形学中广告牌技术的相似性。两者均采用在三维空间中定位、定向与缩放的半透明二维平面几何体。然而，二维高斯泼溅为每个泼溅点使用单一纯色并通过高斯分布调制不透明度，而广告牌技术则更具表现力，可通过uv参数化纹理调制色彩。我们提出通过引入高斯广告牌来统一这两种概念，该方法通过对二维高斯泼溅进行改进，利用逐泼溅点纹理插值实现空间变化的色彩效果。最终形成融合两种表征优势的混合方案，既继承了二维高斯泼溅强大的场景优化能力，又兼具纹理映射的表现力。通过大量定性与定量评估，我们证明相较于原始二维高斯泼溅实现方案，本方法能显著提升场景表征的锐度与质量。