3D-HGS: 3D Half-Gaussian Splatting
This work improves rendering quality for 3D scene reconstruction applications, but it is incremental as it builds directly on 3D Gaussian Splatting.
The paper tackles the problem of shape and color discontinuities in 3D Gaussian Splatting for photo-realistic image rendering by proposing 3D Half-Gaussian kernels as a plug-and-play solution, achieving state-of-the-art rendering quality without speed loss.
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.