Efficient Density Control for 3D Gaussian Splatting

• URL: http://arxiv.org/abs/2411.10133v3
• Date: Tue, 11 Mar 2025 07:14:43 GMT
• Title: Efficient Density Control for 3D Gaussian Splatting
• Authors: Xiaobin Deng, Changyu Diao, Min Li, Ruohan Yu, Duanqing Xu,
• Abstract summary: 3D Gaussian Splatting (3DGS) has demonstrated outstanding performance in novel view synthesis.<n>We propose two key innovations: (1) Long-Axis Split, which precisely controls the position, shape, and opacity of child Gaussians; and (2) Recovery-Aware Pruning, which leverages differences in recovery speed after resetting opacity to prune overfitted Gaussians.
• Score: 3.6379656024631215
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 3D Gaussian Splatting (3DGS) has demonstrated outstanding performance in novel view synthesis, achieving a balance between rendering quality and real-time performance. 3DGS employs Adaptive Density Control (ADC) to increase the number of Gaussians. However, the clone and split operations within ADC are not sufficiently efficient, impacting optimization speed and detail recovery. Additionally, overfitted Gaussians that affect rendering quality may exist, and the original ADC is unable to remove them. To address these issues, we propose two key innovations: (1) Long-Axis Split, which precisely controls the position, shape, and opacity of child Gaussians to minimize the difference before and after splitting. (2) Recovery-Aware Pruning, which leverages differences in recovery speed after resetting opacity to prune overfitted Gaussians, thereby improving generalization performance. Experimental results show that our method significantly enhances rendering quality. Code is available at https://github.com/XiaoBin2001/EDC.

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