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

翻译：近期兴起的3D高斯溅射（3DGS）技术标志着实时新视角合成领域的重大突破。然而，基于3DGS的算法快速涌现，催生了对标准化、综合性评估工具的迫切需求，尤其在压缩任务方面。现有基准测试往往缺乏全面评估不同方法独特特性所需的特定指标，例如渲染速度、率失真权衡、内存效率以及几何精度。为填补这一空白，我们推出了Splatwizard——一个专为3DGS压缩模型基准测试设计的统一工具包。该工具包提供易于使用的框架，既能实现新的3DGS压缩模型，又能利用先前研究提出的前沿技术。此外，框架还集成了自动化计算关键性能指标的流程，包括基于图像的质量指标、重建网格的倒角距离、渲染帧率以及计算资源消耗。代码开源地址：https://github.com/splatwizard/splatwizard