AI 3D
street_gaussians
A utility for eCCV 2024] Street Gaussians: Modeling Dynamic Urban Scenes.
★ 1.4k starsNOASSERTION
View guide →LiDAR-augmented Gaussian Splatting plus neural SDF, in real time.
GS-SDF is an open-source ai 3d project by hku-mars (hku-mars/GS-SDF on GitHub). It has 535 GitHub stars and 44 forks, is released under the GPL-2.0 license, and was last updated on GitHub on 16 July 2026.
Start at the project page.
Get the C++ implementation.
Follow the README build steps.
Fuse LiDAR with splatting.
Depth data guides the splats.
Implicit surfaces for geometry.
Runs live, not offline.
Peer-reviewed robotics research.
Performance-first code.
Paper and demos online.
Download the source and enter the folder.
git clone https://github.com/hku-mars/GS-SDF.git
cd GS-SDFSet up CMake per the README.
cmake -B build -DCMAKE_BUILD_TYPE=ReleaseBuild, then follow the data instructions.
cmake --build build --parallelLiDAR-augmented Gaussian Splatting with neural SDF from an IROS 2025 paper, at hku-mars/GS-SDF.
Depth measurements keep the reconstructed geometry consistent.
Yes, that is a core claim of the work.
The code is open under GPL-2.0.
Robotics and 3D vision researchers.
A utility for eCCV 2024] Street Gaussians: Modeling Dynamic Urban Scenes.
(ICCV 2025) GaussianOcc: Entirely Self-supervised and Efficient 3D Occupancy
Vulkan viewer rendering 3D Gaussians via rasterization and raytracing.
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Nerfstudio — the plug-and-play studio for NeRFs and Gaussian splatting: turn photos of a real scene into explorable 3D, with a modular API and viewer, Apache-2.0
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Free and open — grab the source, star the repo, and start creating.