用几何高斯替代传统贴图，解决贴图拉伸和内存浪费问题
Heat Kernel Textures: the Geodesic Gaussians That Do Not Splat
- 基于曲面几何的各向异性热核，实现无投影贴图
- 消除接缝、失真和重复顶点，内存占用大幅降低
- 适用于多视角图像优化，兼容物理渲染器
3D高斯点阵最近革新了新视角合成及诸多3D视觉方法。受此启发，本文重新思考纹理表示，以克服UV映射带来的主要问题，并显著降低内存开销。热核纹理（HKTex）摒弃了UV展开，彻底解决了空余UV空间、接缝、形变、顶点重复和分辨率不均等问题。该方法基于离散黎曼几何，在三角网格定义的任意曲面流形上内在定义，采用各向异性热核作为测地线等效的高斯函数。与传统方法不同，其位置优化与自适应稠密化策略均在物体表面进行。该新型表示完全集成于物理基础渲染器中，可从现有纹理或多视角图像中优化。项目主页与代码见 circle-group.github.io/research/HeatKernelTextures。
原文摘要 · Abstract (English)
3D Gaussian Splatting has recently revolutionised novel view synthesis as well as many other 3D vision methods and applications. Drawing inspiration from this representation, we now rethink textures to overcome the main issues of UV mapping while considerably lowering their memory footprint. Heat Kernel Textures (HKTex) eliminate UV unwrapping as well as their persistent issues of wasted UV space, seams, distortions, vertex-duplication, and varying resolution. Grounded in discrete Riemannian geometry and intrinsically defined on any manifold surface discretised as a triangular mesh, HKTex uses anisotropic heat kernels as geodesic equivalents to Gaussians. Like our kernels, also the optimisation of their position and the adaptive densification strategies were redefined to operate on the surface of the object to be textureised. Our novel representation is also fully integrated with a physically based renderer and can be optimised either from existing textures or multi-view images. Our project page and code are available at circle-group.github.io/research/HeatKernelTextures.
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