A CUDA-parallel voxelizer and hierarchical SGGX clustering representation enable faster, more accurate level-of-detail rendering of sparse microgeometry volumes.
Sparse voxels rasterization: Real-time high- fidelity radiance field rendering
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
verdicts
UNVERDICTED 3representative citing papers
SaLF is a sparse voxel-based volumetric representation with local implicit fields that supports fast rasterization and raytracing for unified camera and LiDAR simulation in driving scenes.
4D Neural Voxel Splatting uses a compact neural voxel set with deformation fields instead of per-timestamp Gaussians to cut memory and speed training for dynamic scene rendering while keeping image quality.
citing papers explorer
-
Fast Voxelization and Level of Detail for Microgeometry Rendering
A CUDA-parallel voxelizer and hierarchical SGGX clustering representation enable faster, more accurate level-of-detail rendering of sparse microgeometry volumes.
-
SaLF: Sparse Local Fields for Multi-Sensor Rendering in Real-Time
SaLF is a sparse voxel-based volumetric representation with local implicit fields that supports fast rasterization and raytracing for unified camera and LiDAR simulation in driving scenes.
-
4D Neural Voxel Splatting: Dynamic Scene Rendering with Voxelized Guassian Splatting
4D Neural Voxel Splatting uses a compact neural voxel set with deformation fields instead of per-timestamp Gaussians to cut memory and speed training for dynamic scene rendering while keeping image quality.