arXiv (All)
open access
Heat Kernel Textures: the Geodesic Gaussians That Do Not Splat
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 Ke
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- 2Xplat: Decoupling Geometry and Appearance Modeling for Feed-Forward 3D Gaussian Splatting#635777
- 2Xplat: Decoupling Geometry and Appearance Modeling for Feed-Forward 3D Gaussian Splatting#633428
- StereoGaussians: Feed-Forward 3D Gaussian Splatting from Stereo Images#1143193
- X-GS: An Extensible Framework for Perceiving and Thinking with 3D Gaussian Splatting#1048589
- LG-HCC: Local Geometry-Aware Hierarchical Context Compression for 3D Gaussian Splatting#1036658
Record · ID 984471
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive