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View guide →// ai-3d · GANWANSHUI/GaussianOcc
GaussianOcc
GaussianOcc is an open-source ai 3d project by GANWANSHUI (GANWANSHUI/GaussianOcc on GitHub). It has 385 GitHub stars and 21 forks, is released under the Apache-2.0 license, and was last updated on GitHub on 17 February 2026.
(ICCV 2025) GaussianOcc: Entirely Self-supervised and Efficient 3D Occupancy
💎 Hidden gem★ 385 stars⑂ 21 forksApache-2.0updated 2026-02
▦ visual — this project's README ships no embeddable screenshot,
so here's a placeholder. The guide below is complete regardless.
so here's a placeholder. The guide below is complete regardless.
// project facts
Project facts
- Repository
- GANWANSHUI/GaussianOcc
- GitHub stars
- 385
- Forks
- 21
- License
- Apache-2.0
- Last updated on GitHub
- 17 February 2026
- Category
- AI 3D
- Listing
- Hidden gem — a shorter page for a lesser-known project
- Official site
- Official site
// how it works
How it works
- Get the code
Clone GANWANSHUI/GaussianOcc and move into the project folder.
- Install dependencies
Install the Python requirements with pip — a virtual environment keeps things clean.
- Prepare inputs
Gather the images or data the model expects.
- Run reconstruction
Launch training or inference and inspect the 3D output.
// features
Why people love it
Written in Python
Python codebase — approachable for contributors.
Apache-2.0
Apache-2.0 licensed — permissive, with a patent grant.
Open development
Public repo — issues and pull requests are welcome.
Community-driven
Fork it and make it your own.
Growing project
A growing community of users and contributors.
Source available
Read, audit, and learn from the full source.
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// run it
Run it yourself
- Step 1 — Clone the repo
Download the source and move into the project folder.
git clone https://github.com/GANWANSHUI/GaussianOcc.git cd GaussianOcc - Step 2 — Install dependencies
Set up what the project needs to run.
pip install -r requirements.txt - Step 3 — Run it
Start the app — the README has the exact command and flags.
python main.py # entrypoint varies — check the README
// use cases
What you can build
- Render novel views from sparse inputs.
- Study the latest 3D research code.
- Reconstruct 3D scenes from photos.
- Generate 3D assets with AI.
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// faq
Questions, answered
What license is it under?
Apache-2.0 licensed — permissive, with a patent grant.
How hard is it to install?
Clone the repo and pip-install the requirements — the README covers the exact steps.
Where do I get help?
The GitHub repo's issues and discussions are the main support channel.
Is the project still maintained?
Last pushed 2026-02-17 with 21 forks. Skim recent commits to gauge momentum before relying on it.
Can I contribute?
Yes — it is open source, so issues and pull requests are welcome.
// keep exploring
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// more in ai-3d
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Get GaussianOcc
Free and open — grab the source, star the repo, and start creating.