Splatwizard: A Benchmark Toolkit for 3D Gaussian Splatting Compression

Xiang Liu, Yimin Zhou, Jinxiang Wang, Yujun Huang, Shuzhao Xie +7 more
12/31/2025
cs.CV

Official code: splatwizard/splatwizard (31 stars, MIT, last commit 2026-01-06).

Abstract

The recent advent of 3D Gaussian Splatting (3DGS) has marked a significant breakthrough in real-time novel view synthesis. However, the rapid proliferation of 3DGS-based algorithms has created a pressing need for standardized and comprehensive evaluation tools, especially for compression task. Existing benchmarks often lack the specific metrics necessary to holistically assess the unique characteristics of different methods, such as rendering speed, rate distortion trade-offs memory efficiency, and geometric accuracy. To address this gap, we introduce Splatwizard, a unified benchmark toolkit designed specifically for benchmarking 3DGS compression models. Splatwizard provides an easy-to-use framework to implement new 3DGS compression model and utilize state-of-the-art techniques proposed by previous work. Besides, an integrated pipeline that automates the calculation of key performance indicators, including image-based quality metrics, chamfer distance of reconstruct mesh, rendering frame rates, and computational resource consumption is included in the framework as well. Code is available at https://github.com/splatwizard/splatwizard

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Code Implementations(1)

MIT

Toolkit for 3DGS compression research

313C, C++Nov 25, 20259 months agoMIT

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Cite this paper

@article{liu2025splatwizard,
  title  = {Splatwizard: A Benchmark Toolkit for 3D Gaussian Splatting Compression},
  author = {Xiang Liu and Yimin Zhou and Jinxiang Wang and Yujun Huang and Shuzhao Xie and Shiyu Qin and Mingyao Hong and Jiawei Li and Yaowei Wang and Zhi Wang and Shu-Tao Xia and Bin Chen},
  year   = {2025},
  eprint = {2512.24742},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2512.24742v1}
}

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