Splatwizard: A Benchmark Toolkit for 3D Gaussian Splatting Compression
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Abstract (arXiv)
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
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 40 of its 49 references that are in the map. First posted on arXiv 31 Dec 2025.
Builds on
40 of 49 references.
References · 40
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28 more
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Citing papers per year: 2026: 2.
2 papers.