mlsanityData to 7 Oct 2026

Heat Kernel Textures: the Geodesic Gaussians That Do Not Splat

arXiv 2609.07557 ↗First posted 7 Sep 2026cs.CV cs.GR cs.LGcited by 1

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 25 of its 52 references that are in the map. First posted on arXiv 7 Sep 2026.

Builds on

25 of 52 references.

References · 25

  1. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
  2. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,698
  3. 2017Billion-scale similarity search with GPUscited by 2,477
  4. 2019Optuna: A Next-generation Hyperparameter Optimization Frameworkcited by 2,455
  5. 2022Objaverse: A Universe of Annotated 3D Objectscited by 1,522
  6. 2023SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Renderingcited by 611
  7. 2021Extracting Triangular 3D Models, Materials, and Lighting From Imagescited by 363
  8. 2019Texture Fields: Learning Texture Representations in Function Spacecited by 210
  9. 2023Relightable 3D Gaussians: Realistic Point Cloud Relighting with BRDF Decomposition and Ray Tracingcited by 138
  10. 2021NeuTex: Neural Texture Mapping for Volumetric Neural Renderingcited by 98
  11. 2024GaussianImage: 1000 FPS Image Representation and Compression by 2D Gaussian Splattingcited by 97
  12. 2024Texture-GS: Disentangling the Geometry and Texture for 3D Gaussian Splatting Editingcited by 47
13 more
  1. 2024Don't Splat your Gaussians: Volumetric Ray-Traced Primitives for Modeling and Rendering Scattering and Emissive Mediacited by 37
  2. 2024Image-GS: Content-Adaptive Image Representation via 2D Gaussianscited by 34
  3. 2018The Vector Heat Methodcited by 31
  4. 2025Large Images are Gaussians: High-Quality Large Image Representation with Levels of 2D Gaussian Splattingcited by 28
  5. 2024GeoSplatting: Towards Geometry Guided Gaussian Splatting for Physically-based Inverse Renderingcited by 22
  6. 2022Intrinsic Neural Fields: Learning Functions on Manifoldscited by 20
  7. 2024MeshGS: Adaptive Mesh-Aligned Gaussian Splatting for High-Quality Renderingcited by 19
  8. 2025Neural Shell Texture Splatting: More Details and Fewer Primitivescited by 14
  9. 2025UVGS: Reimagining Unstructured 3D Gaussian Splatting using UV Mappingcited by 8
  10. 2024Uncertainty for SVBRDF Acquisition using Frequency Analysiscited by 4
  11. 2014Unified Heat Kernel Regression for Diffusion, Kernel Smoothing and Wavelets on Manifolds and Its Application to Mandible Growth Modeling in CT Imagescited by 3
  12. 2024MeshFeat: Multi-Resolution Features for Neural Fields on Meshescited by 3
  13. 2026Parallelised Differentiable Straightest Geodesics for 3D Meshescited by 2

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Citing papers per year: 2026: 1.

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