TileSkipper: Region-Adaptive Tile Pruning for 3D Gaussian Splatting
Tiled 3D Gaussian Splatting rasterizers often use one scene-wide contribution cutoff for tile enumeration, although content differs in its sensitivity to support truncation.
ProofPaper ↗
Key points
- TileSkipper selects a static per-Gaussian cutoff policy for a frozen checkpoint.
- Across 13 scenes from Mip-NeRF 360, Tanks & Temples, and Deep Blending, a fixed-policy AccuTile sweep gives dataset-macro speedups of $1.088\times$ at standard resolution and $1.238\times$ at 3840 pixels wide, with $-0.007/-0.023$ dB mean PSNR change.
- For four ports from $3σ$ rasterizers, we separately attribute the prior exact-bound transition and our incremental gain.
- Matched-quality ablations show modest gains over scene-global calibration and parity with per-Gaussian control; the standalone comparison with AdaGScale is regime-dependent.
Sources (1)
- [1]TileSkipper: Region-Adaptive Tile Pruning for 3D Gaussian SplattingarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 7, 03:01 AM
Tiled 3D Gaussian Splatting rasterizers often use one scene-wide contribution cutoff for tile enumeration, although content differs in its sensitivity to support truncation.
TileSkipper selects a static per-Gaussian cutoff policy for a frozen checkpoint.
Extractive summary: sentences quoted from the sources.