Frequency-Aware Density Control via Reparameterization for High-Quality Rendering of 3D Gaussian Splatting
This work addresses a specific bottleneck in 3DGS rendering for improving scene detail representation, making it an incremental advancement in the field.
The paper tackles the problem of 3D Gaussian Splatting (3DGS) losing accuracy by using improper-scale Gaussians to represent high-frequency details, and proposes a frequency-aware density control strategy via reparameterization, which outperforms state-of-the-art methods on various datasets.
By adaptively controlling the density and generating more Gaussians in regions with high-frequency information, 3D Gaussian Splatting (3DGS) can better represent scene details. From the signal processing perspective, representing details usually needs more Gaussians with relatively smaller scales. However, 3DGS currently lacks an explicit constraint linking the density and scale of 3D Gaussians across the domain, leading to 3DGS using improper-scale Gaussians to express frequency information, resulting in the loss of accuracy. In this paper, we propose to establish a direct relation between density and scale through the reparameterization of the scaling parameters and ensure the consistency between them via explicit constraints (i.e., density responds well to changes in frequency). Furthermore, we develop a frequency-aware density control strategy, consisting of densification and deletion, to improve representation quality with fewer Gaussians. A dynamic threshold encourages densification in high-frequency regions, while a scale-based filter deletes Gaussians with improper scale. Experimental results on various datasets demonstrate that our method outperforms existing state-of-the-art methods quantitatively and qualitatively.