Spectral-GS: Taming 3D Gaussian Splatting with Spectral Entropy

• URL: http://arxiv.org/abs/2409.12771v2
• Date: Tue, 15 Oct 2024 07:35:49 GMT
• Title: Spectral-GS: Taming 3D Gaussian Splatting with Spectral Entropy
• Authors: Letian Huang, Jie Guo, Jialin Dan, Ruoyu Fu, Shujie Wang, Yuanqi Li, Yanwen Guo,
• Abstract summary: 3D-GS lacks shape awareness, relying instead on spectral radius and view positional gradients to determine splitting. Our Spectral-GS, based on spectral analysis, introduces 3D shape-aware splitting and 2D view-consistent filtering strategies.
• Score: 14.320240635262756
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Recently, 3D Gaussian Splatting (3D-GS) has achieved impressive results in novel view synthesis, demonstrating high fidelity and efficiency. However, it easily exhibits needle-like artifacts, especially when increasing the sampling rate. Mip-Splatting tries to remove these artifacts with a 3D smoothing filter for frequency constraints and a 2D Mip filter for approximated supersampling. Unfortunately, it tends to produce over-blurred results, and sometimes needle-like Gaussians still persist. Our spectral analysis of the covariance matrix during optimization and densification reveals that current 3D-GS lacks shape awareness, relying instead on spectral radius and view positional gradients to determine splitting. As a result, needle-like Gaussians with small positional gradients and low spectral entropy fail to split and overfit high-frequency details. Furthermore, both the filters used in 3D-GS and Mip-Splatting reduce the spectral entropy and increase the condition number during zooming in to synthesize novel view, causing view inconsistencies and more pronounced artifacts. Our Spectral-GS, based on spectral analysis, introduces 3D shape-aware splitting and 2D view-consistent filtering strategies, effectively addressing these issues, enhancing 3D-GS's capability to represent high-frequency details without noticeable artifacts, and achieving high-quality photorealistic rendering.

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