A publication-quality visualization tool for 3D Gaussian Splatting (3DGS) researchers to generate static and interactive radar charts, comparison tables, and evolution timelines.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install 3dgs-visualizer
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install 3dgs-visualizer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is 3DGS Visualizer?
The 3DGS Visualizer is a specialized visualization engine designed for academic and professional researchers studying 3D Gaussian Splatting. Finding high-quality tools that seamlessly convert complex empirical tables and chronological lineages into paper-ready figures can be challenging. This tool is part of the ecosystem of Openclaw Skills, helping developers and AI agents automatically generate outstanding, colorblind-accessible visual assets directly from markdown references.
By leveraging matplotlib and plotly, the visualizer generates dual-output formats—static PDF/PNG files formatted specifically for LaTeX and scientific papers, and interactive HTML charts ideal for conference presentations and web-based documentation. From speed-versus-quality scatter plots to categorical evolution timelines, it streamlines the visual representation of state-of-the-art 3D reconstruction models.
3DGS Visualizer Use Cases
- Generating publication-ready visual assets (PDF/PNG) at 300 DPI for conference and journal paper submissions.
- Creating interactive HTML timelines and radar comparison tables for team presentations or open-source project websites.
- Synthesizing multidimensional benchmark comparisons (FPS, PSNR, VRAM) across various 3DGS baselines.
- Automatically mapping the historical lineage and categorical evolution of 3D Gaussian Splatting variants.
How 3DGS Visualizer Works
- Identify Requirements: Specify the target visualization type (radar chart, comparison table, or chronological timeline), baseline methods, and required formats (PDF, PNG, or HTML).
- Scan Reference Data: The agent scans internal reference markdown files (e.g.,
methods-core.md,experiments.md) to extract numerical performance metrics and paper metadata. - Build Execution Script: The system generates a clean, self-contained Python script using configured visualization packages inside a temporary workspace directory.
- Apply Style & Styling Rules: Automatic application of scientific layout principles, including the colorblind-friendly Okabe-Ito color palette and uniform category colors.
- Compile & Export: Run the script to produce publication-grade static vectors (PDF) and interactive visual components (HTML) side by side.
3DGS Visualizer Setup
To get started with this visualizer in your Openclaw environment, ensure you have Python installed with the necessary scientific plotting libraries.
pip install numpy matplotlib plotly pandas
Configure your local workspace structure to include the standard 3DGS dataset indices in your local references/ folder. Once references are configured, use the Openclaw Skills suite to trigger automated script generation.
3DGS Visualizer Data Schema & Taxonomy
The visualizer processes markdown reference databases and maps categories to standardized color palettes. Here is how your data files and styling properties should align:
Input References Folder
| File Path | Description |
|---|---|
references/3dgs-methods-overview.md |
Master index of 3DGS methods and overview metrics |
references/methods-core.md |
Core geometry, generation, and baseline definitions |
references/experiments.md |
Empirical datasets and performance benchmarks |
Standard Category Colors
All visualizations share a unified color theme to ensure consistent representation across charts:
- Foundation:
#0072B2(Deep Blue) - Compression:
#E69F00(Orange) - Feed-Forward:
#009E73(Green) - Geometry / Surface:
#D55E00(Rust Red) - Dynamic:
#CC79A7(Pink) - Avatar / Human:
#994F00(Brown)
3DGS Visualizer Advanced Features
- Preset Combinations: Offers packaged presets like the 'Paper Submission Package' which outputs a radar chart, performance matrix, and efficiency scatter plot in one run.
- Colorblind-Friendly Okabe-Ito Defaulting: Applies the Okabe-Ito color palette by default to all radar comparisons, ensuring accessibility.
- Automatic Best-in-Class Highlighting: Compiles tables with automated visual color-coding to highlight first-place (green) and second-place (blue) metric performers.
- Dynamic Layout Refinement: Suppresses 'chart junk' such as shadows and redundant grids to comply with rigid IEEE and ACM formatting guidelines.
SKILL.md
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