发表机构
Imperial College London（帝国理工学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
受三维高斯抛雪启发，提出热核纹理（HKTex），用测地高斯替代高斯抛雪，消除UV展开问题并降低内存，支持从纹理或多视角图像优化。
AI 中文摘要
三维高斯抛雪（3D Gaussian Splatting）最近彻底改变了新视角合成以及许多其他三维视觉方法和应用。受这种表示的启发，我们现在重新思考纹理，以克服UV映射的主要问题，同时显著降低其内存占用。热核纹理（HKTex）消除了UV展开及其持久性问题，如UV空间浪费、接缝、畸变、顶点重复和分辨率变化。基于离散黎曼几何，并固有地定义在任何以三角网格离散化的流形表面上，HKTex使用各向异性热核作为高斯的测地等效物。与我们的核一样，其位置的优化和自适应加密策略也被重新定义，以在待纹理化对象的表面上操作。我们的新表示还与基于物理的渲染器完全集成，并且可以从现有纹理或多视角图像进行优化。我们的项目页面和代码可在该HTTP URL获取。
英文摘要
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.
CommentsECCV 2026 (Long Oral)
