3DGS.zip: A survey on 3D Gaussian Splatting Compression Methods

This repository contains a comprehensive survey of 3D Gaussian Splatting (3DGS) compression methods. You can view the full survey table and comparison plots at w-m.github.io/3dgs-compression-survey/.

Installation

To run the scripts in this repository, ensure you have all necessary dependencies installed. You can install them using the following command:

pip install -r requirements.txt

Building the Site

To build the site, use the following command:

python data_extraction/build_html.py

This scrips also runs automatically to rebuild the site whenever changes are pushed to the main branch.

Fetching Results

You can fetch the results automatically by running:

python data_extraction/data_extraction.py

This script attempts to fetch data from the relevant papers and update the tables in the results folder. To add a new paper, create an entry in data_extraction/data_source.yaml.

Including your own Results

Authors are kindly requested to upload their per-scene results in a designated folder within their GitHub repository. This ensures accurate data retrieval and allows for consistent and fair comparisons. The expected folder structure is:

results
├── DeepBlending
│   ├── drjohnson.csv
│   └── playroom.csv
├── MipNeRF360
│   ├── bicycle.csv
│   ├── bonsai.csv
│   ├── counter.csv
│   ├── flowers.csv
│   ├── garden.csv
│   ├── kitchen.csv
│   ├── room.csv
│   ├── stump.csv
│   └── treehill.csv
├── SyntheticNeRF
│   ├── chair.csv
│   ├── drums.csv
│   ├── ficus.csv
│   ├── hotdog.csv
│   ├── lego.csv 
│   ├── materials.csv
│   ├── mic.csv
│   └── ship.csv
└── TanksAndTemples
    ├── train.csv
    └── truck.csv

The folder should include all datasets on which your method was evaluated and cover all scenes specified in the folder structure.

Each CSV file should be structured as follows:

Submethod,PSNR,SSIM,LPIPS,Size [Bytes],#Gaussians
Baseline,xx.xx,0.xxx,0.xxx,xxxxxxxx,xxxxxxxx
-SubmethodName,xx.xx,0.xxx,0.xxx,xxxxxxxx,xxxxxxxx
,xx.xx,0.xxx,0.xxx,xxxxxxxx,xxxxxxxx
,xx.xx,0.xxx,0.xxx,xxxxxxxx,xxxxxxxx
,xx.xx,0.xxx,0.xxx,xxxxxxxx,xxxxxxxx

Include up to two consistent submethod names for your results across all files to ensure they appear in the survey table. These names will then be concatenated with the name of your approach in the table. If you prefer only the name of your approach to be displayed in the table, you can use "Baseline" as a submethod name for those results. Results without a submethod name will only be displayed in the plots.

You can view an example here

LaTeX Table

An up-to-date LaTeX version of the survey table can be found here here. Feel free to copy a line from the table into your research if you want to compare to the approach. Should you wish to copy the whole table you might need the following packages and definitions in your LaTeX preamble:

\usepackage{booktabs}
\usepackage[table]{xcolor}
% colors for table
\definecolor{lightred}{HTML}{FF9999}
\definecolor{lightyellow}{HTML}{FFFF99}
\definecolor{lightorange}{HTML}{FFCC99}
\usepackage{makecell}
\usepackage{adjustbox}
% make text the same size even when its bold in a table
\newsavebox\CBox
\def\textBF#1{\sbox\CBox{#1}\resizebox{\wd\CBox}{\ht\CBox}{\textbf{#1}}}

Citation

If you use our survey in your research, please cite our work. You can use the following BibTeX entry:

@misc{3DGSzip2024,
    title={3DGS.zip: A survey on 3D Gaussian Splatting Compression Methods}, 
    author={Milena T. Bagdasarian and Paul Knoll and Florian Barthel and Anna Hilsmann and 
            Peter Eisert and Wieland Morgenstern},
    year={2024},
    eprint={2407.09510},
    archivePrefix={arXiv},
    primaryClass={cs.CV},
    url={https://arxiv.org/abs/2407.09510}, 
}