English

3D-HGS: 3D Half-Gaussian Splatting

Computer Vision and Pattern Recognition 2025-05-07 v4 Graphics

Abstract

Photo-realistic image rendering from 3D scene reconstruction has advanced significantly with neural rendering techniques. Among these, 3D Gaussian Splatting (3D-GS) outperforms Neural Radiance Fields (NeRFs) in quality and speed but struggles with shape and color discontinuities. We propose 3D Half-Gaussian (3D-HGS) kernels as a plug-and-play solution to address these limitations. Our experiments show that 3D-HGS enhances existing 3D-GS methods, achieving state-of-the-art rendering quality without compromising speed.

Keywords

Cite

@article{arxiv.2406.02720,
  title  = {3D-HGS: 3D Half-Gaussian Splatting},
  author = {Haolin Li and Jinyang Liu and Mario Sznaier and Octavia Camps},
  journal= {arXiv preprint arXiv:2406.02720},
  year   = {2025}
}

Comments

8 pages, 9 figures

R2 v1 2026-06-28T16:53:36.846Z