arXiv (All)
open access
Gaussian Stippling: Efficient Sorting-Free 3D Gaussian Rendering through Hybrid Sampling and Spatiotemporal Reconstruction
Conventional 3D Gaussian Splatting (3DGS) requires depth sorting and ordered alpha blending to correctly render overlapping Gaussian primitives. Stochastic transparency enables sorting-free rendering by replacing fractional alpha contributions with discrete stochastic visibility samples, but produce
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
- SSA-3DGS: Unsupervised Removal of Screen-Space Artifacts for 3D Gaussian Splatting#1012259
- MEGA: Object-Level Mesh Extraction from 3D Gaussian Splatting via Spatial Visual Distillation#1156978
- From Splats to Silicon: Rethinking Computational Efficiency of 3DGS#973759
- MoQSplat: Adaptive Progressive Streaming of 3D Gaussian Splatting via MoQ#1012799
- MoQSplat: Adaptive Progressive Streaming of 3D Gaussian Splatting via MoQ#965369
Record · ID 1143089
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