3D-HGS: 3D Half-Gaussian Splatting

Haolin Li, Jinyang Liu, Mario Sznaier, Octavia Camps

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.