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3D-HGS: 3D Half-Gaussian Splatting

About

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.

Haolin Li, Jinyang Liu, Mario Sznaier, Octavia Camps• 2024

Related benchmarks

TaskDatasetResultRank
Novel View SynthesisMip-NeRF 360 (test)
PSNR33.5
199
Novel View SynthesisMip-NeRF360
PSNR29.61
184
Novel View SynthesisDeep Blending (test)
PSNR29.8
80
Novel View SynthesisDeep Blending
PSNR29.76
80
Novel View SynthesisMip-NeRF360 (test)
PSNR26.74
80
Novel View SynthesisNeRF Synthetic (test)--
46
Novel View SynthesisTanks&Temples
PSNR24.17
44
Novel View SynthesisMip-NeRF 360
PSNR29.772
37
Novel View SynthesisDeep Blending
SSIM90.5
32
Novel View SynthesisTank & Temples (test)
PSNR25.08
23
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