Splatwizard: A Benchmark Toolkit for 3D Gaussian Splatting Compression
This provides a unified framework for researchers in 3D computer vision to benchmark compression models, though it is incremental as it builds on existing methods without proposing new algorithms.
The authors tackled the lack of standardized evaluation tools for 3D Gaussian Splatting compression by introducing Splatwizard, a benchmark toolkit that automates performance metrics like image quality, rendering speed, and resource consumption.
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