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3D-HGS: 3D Half-Gaussian Splatting
June 04, 2024 Β· Declared Dead Β· π Computer Vision and Pattern Recognition
"No code URL or promise found in abstract"
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Authors
Haolin Li, Jinyang Liu, Mario Sznaier, Octavia Camps
arXiv ID
2406.02720
Category
cs.CV: Computer Vision
Cross-listed
cs.GR
Citations
34
Venue
Computer Vision and Pattern Recognition
Last Checked
4 months ago
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.
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