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Snapshot 0 · 2026-11-04T12:47:27Z · Python · MIT
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GitHub description at capture

Curated list of papers and resources focused on 3D Gaussian Splatting, intended to keep pace with the anticipated surge of research in the coming months.
README at capture

# Awesome 3D Gaussian Splatting

<div align="center">
  A curated collection of resources focused on 3D Gaussian Splatting (3DGS) and related technologies.

  [**Browse the Paper List**](https://mrnerf.github.io/awesome-3D-gaussian-splatting/) | [**LichtFeld Studio**](https://lichtfeld.io) | [**Contribute**](CONTRIBUTING.md) | [**MrNeRF**](https://www.mrnerf.com)

</div>

## Contents

- [Papers &amp; Documentation](#papers--documentation)
- [Implementations](#implementations)
- [Viewers &amp; Game Engine Support](#viewers--game-engine-support)
- [Tools &amp; Utilities](#tools--utilities)
- [Learning Resources](#learning-resources)
- [Credits](#credits)

## Papers & Documentation

### Papers Database

Visit our comprehensive, searchable database of 3D Gaussian Splatting papers:
[Papers Database](https://mrnerf.github.io/awesome-3D-gaussian-splatting/)

### Courses & Tutorials

- [MIT Inverse Rendering Lectures (Module 2)](https://www.scenerepresentations.org/courses/inverse-graphics-23/) - Academic deep dive into inverse rendering
- [3DGS Tutorial](https://3dgstutorial.github.io/) - Tutorial from the authors of the original 3DGS paper

### Datasets

- [NERDS 360 Multi-View dataset](https://zubair-irshad.github.io/projects/neo360.html) - High-quality outdoor scene dataset

## Implementations

### Official Reference

- [Original Gaussian Splatting](https://github.com/graphdeco-inria/gaussian-splatting) - The reference implementation by the original authors

### Community Implementations

| Implementation | Language | License | Description |
| -------------- | -------- | ------- | ----------- |
| [LichtFeld Studio](https://github.com/MrNeRF/LichtFeld-Studio) ([lichtfeld.io](https://lichtfeld.io)) | C++/CUDA | GPL-3.0 | The modular workstation for 3D Gaussian Splatting — train, inspect, edit, automate, and export from a single native app |
| [Nerfstudio gsplat](https://github.com/nerfstudio-project/gsplat) | Python/CUDA | Apache-2.0 | Integration with Nerfstudio |
| [OpenSplat](https://github.com/pierotofy/OpenSplat) | C++/CPU/GPU | AGPL-3.0 | Cross-platform solution |
| [Taichi 3D GS](https://github.com/wanmeihuali/taichi_3d_gaussian_splatting) | Taichi | Apache-2.0 | Taichi-based implementation |
| [taichi-splatting](https://github.com/uc-vision/taichi-splatting) | Taichi/PyTorch | Apache-2.0 | Modular rasterizer for Taichi and PyTorch |
| [Grendel Distributed 3DGS](https://github.com/nyu-systems/Grendel-GS) | Python/CUDA | Apache-2.0 | Multi-GPU distributed training |
| [Warp 3DGS](https://github.com/guoriyue/3dgs-warp-scratch) | Warp/Python | AGPL-3.0 | Warp-based implementation |
| [RI3D](https://github.com/Asus-Monitor/ri3d-impl) | Python/CUDA | Unlicense | Few-shot gaussian splatting pipeline |
| [gaussian_splatting](https://github.com/joeyan/gaussian_splatting) | Python/CUDA | MIT | Readable implementation with a [written derivation of the math](https://github.com/joeyan/gaussian_splatting/blob/main/MATH.md) |
| [3d-gaussian-splatting](https://github.com/WangFeng18/3d-gaussian-splatting) | Python/CUDA | MIT | Compact reimplementation |
| [gaussian_splatting_3d](https://github.com/heheyas/gaussian_splatting_3d) | Python/CUDA | | Early community reimplementation |
| [My-exp-Gaussians](https://github.com/ingra14m/My-exp-Gaussian) | Python/CUDA | | Enhances the ability of 3D Gaussians to model complex scenes |
| [360-gaussian-splatting](https://github.com/inuex35/360-gaussian-splatting) | Python | | Trains splats directly from 360° images |
| [2D Gaussian Splatting](https://github.com/OutofAi/2D-Gaussian-Splatting) | Jupyter | MIT | Notebook walkthrough of 2D gaussian splatting |
| [DGSO](https://github.com/An-u-rag/stylized-gaussian-splatting) | Python | MIT | Style transfer applied during gaussian optimization |
| [3D-Gaussian-Splatting-Reconstruction](https://github.com/Chi-Blaze-B/3D-Gaussian-Splatting-Reconstruction) | Python | Apache-2.0 | Pure PyTorch implementation from video input — no CUDA compilation required, supports CPU/NVIDIA GPU backends, built-in pose estimator & GUI |
| [MetalSplat](https://github.com/tchauffi/metalsplat) | PyTorch/Metal | MIT | Metal-based implementation for Apple Silicon GPUs on PyTorch with automatic kernel compilation at runtime |

### Frameworks

- [Pointrix](https://github.com/pointrix-project/pointrix) - Differentiable point-based rendering
- [msplat](https://github.com/pointrix-project/msplat) - Modular differential gaussian rasterization library
- [GauStudio](https://github.com/GAP-LAB-CUHK-SZ/gaustudio) - Unified framework with multiple implementations
- [DriveStudio](https://github.com/ziyc/drivestudio) - Urban scene reconstruction framework
- [GSCodecStudio](https://github.com/JasonLSC/GSCodec_Studio) - Compression and Dynamic splattings
- [gaussian-splatting-lightning](https://github.com/yzslab/gaussian-splatting-lightning) - Derived algorithms plus an interactive web viewer

## Viewers & Game Engine Support

### Game Engines

- [Unity Plugin](https://github.com/aras-p/UnityGaussianSplatting)
- [Unity Plugin (gsplat-unity)](https://github.com/wuyize25/gsplat-unity)
- [Unity Plugin (DynGsplat-unity)](https://github.com/HiFi-Human/DynGsplat-unity) - For dynamic splattings
- [Unreal Plugin (MLSLabsGaussianSplattingRenderer-UE)](https://github.com/mlslabs/MLSLabsGaussianSplattingRenderer-UE)
- [Unreal Plugin (XScene-UEPlugin)](https://github.com/xverse-engine/XScene-UEPlugin)
- [PlayCanvas Engine](https://github.com/playcanvas/engine)
- [Godot Plugin (gdgs)](https://github.com/ReconWorldLab/godot-gaussian-splatting) - Real-time 3DGS rendering plugin for Godot 4.3+

### Web Viewers

**WebGL**

- [Splat Viewer](https://github.com/antimatter15/splat)
- [Gauzilla](https://github.com/BladeTransformerLLC/gauzilla)
- [Interactive Viewer](https://github.com/kishimisu/Gaussian-Splatting-WebGL)
- [GaussianSplats3D](https://github.com/mkkellogg/GaussianSplats3D)
- [gsplat.js](https://github.com/huggingface/gsplat.js)
- [A-Frame](https://github.com/quadjr/aframe-gaussian-splatting)
- [splaTV](https://github.com/antimatter15/splaTV) - Viewer for 4D Gaussians, with a [live demo](http://antimatter15.com/splaTV/)
- [WebRTC viewer](https://github.com/dylanebert/gaussian-viewer)

**WebGPU**

- [EPFL Viewer](https://github.com/cvlab-epfl/gaussian-splatting-web)
- [WebGPU Splat](https://github.com/KeKsBoTer/web-splat)
- [gaussian-splatting-webgpu](https://github.com/MarcusAndreasSvensson/gaussian-splatting-webgpu)
- [SuperSplat Viewer](https://github.com/playcanvas/supersplat-viewer) - High-performance splat viewer
- [PlayCanvas Model Viewer](https://github.com/playcanvas/model-viewer) - Viewer for glTF and 3DGS assets

### Desktop Viewers

- [3DGS.cpp](https://github.com/shg8/3DGS.cpp) - C++/Vulkan renderer for Windows, macOS, Linux, iOS and visionOS
- [vkgs](https://github.com/jaesung-cs/vkgs) - Cross-platform C++/Vulkan renderer
- [splatviz](https://github.com/Florian-Barthel/splatviz) - Edit the rendering code at runtime or display multiple scenes at once
- [OpenGL Viewer](https://github.com/limacv/GaussianSplattingViewer) - PyOpenGL viewer, also with official CUDA backend
- [Taichi Viewer](https://github.com/uc-vision/splat-viewer) - Renderer with benchmarking capability
- [DearGaussianGUI](https://github.com/leviome/DearGaussianGUI)
- [LiteViz-GS](https://github.com/panxkun/liteviz-gs)
- [Nerfstudio Viser](https://github.com/viser-project/viser)
- [Nerfstudio (gaussian_splatting branch)](https://github.com/yzslab/nerfstudio/tree/gaussian_splatting)
- [Jupyter notebook viewer](https://github.com/shumash/gaussian-splatting/blob/mshugrina/interactive/interactive.ipynb)

### Native Applications

- [Blender Add-on](https://github.com/ReshotAI/gaussian-splatting-blender-addon)
- [Blender Add-on (KIRI)](https://github.com/Kiri-Innovation/3dgs-render-blender-addon)
- [Blender Add-on (404—GEN)](https://github.com/404-Repo/404-gen-blender-add-on)
- [Houdini Viewport Renderer](https://github.com/rubendhz/houdini-gsplat-renderer) - HDK/GLSL implementation of Gaussian Splatting in Houdini
- [iOS Metal Viewer](https://github.com/laanlabs/metal-splats)
- [VR Support (OpenXR)](https://github.com/hyperlogic/splatapult)
- [ROS2 Support](https://github.com/shadygm/ROSplat)
- [Splat Local](https://github.com/michael-L-i/splat-local) - Video-to-3DGS pipeline running fully locally on Apple Silicon (COLMAP/GLOMAP poses, Metal-native training via Brush), with training checkpoints streamed live into a browser viewer

## Tools & Utilities

### Data Processing

- [Kapture](https://github.com/naver/kapture) - Unified data format for visual localization
- [Kapture image cropper](https://gist.github.com/jo-chemla/258e6e40d3d6c2220b29518ff3c17c40) - Undistorted image cropper to remove black borders
- [3DGS Converter](https://github.com/francescofugazzi/3dgsconverter) - Format conversion tool
- [Point Cloud Editor](https://github.com/JohannesKrueger/pointcloudeditor) - Web-based point cloud editing
- [SPZ Converter](https://github.com/stytim/spz) - SPZ conversion tool
- [gsbox Converter](https://github.com/gotoeasy/gsbox) - PLY SPLAT SPZ SPX conversion tool
- [SplatTransform](https://github.com/playcanvas/splat-transform) - CLI tool and Node/browser library for converting and editing splats, reads PLY, SOG, SPZ, SPLAT, KSPLAT and LCC/LCC2, writes PLY, SOG, SPZ, GLB, CSV, LOD and WebP
- [GaussForge](https://github.com/3dgscloud/GaussForge) - C++/WASM-based conversion between PLY, SPZ, SPLAT, and KSPLAT
- [SpectacularAI](https://github.com/SpectacularAI/point-cloud-tools) - Conversion scripts for different 3DGS conventions
- [VGGT Factor Refinement](https://github.com/jashshah999/vggt-factor-refinement) - COLMAP-free pipeline using VGGT + factor graph, from video to COLMAP-format output
- [splatreg](https://github.com/Archerkattri/splatreg) - pip-installable splat registration: align & merge two 3DGS scans into one SE(3)/Sim(3) frame (recovers scale), CLI + pure-PyTorch API, no manual gizmo
- [AURA](https://github.com/Archerkattri/aura) - Calibrated per-splat confidence for 3DGS assets: held-out reliability labels, isotonic calibration, and a distribution-free conformal pruning certificate with a certified LOD ladder; exports via glTF/OpenUSD/SPZ (pip install aura-splat)
- [Open Reality](https://github.com/reality-opened/openreality) - Phone video to a 3D scene (VGGT-SLAM based, splat export with optional gsplat refinement) that an AI assistant can query over MCP: measurements, floor and wall planes, path planning, object list, robot-training exports; self-hostable

### Development Tools

- [GSOPs for Houdini](https://github.com/cgnomads/GSOPs) - Houdini integration tools
- [camorph](https://github.com/Fraunhofer-IIS/camorph) - Camera parameter conversion
- [SuperSplat](https://github.com/playcanvas/supersplat) - Free, open source browser-based 3DGS editor with one-click publishing

## Learning Resources

### Blog Posts

- [3DGS Introduction](https://huggingface.co/blog/gaussian-splatting) - HuggingFace guide
- [Comprehensive overview of Gaussian Splatting](https://towardsdatascience.com/a-comprehensive-overview-of-gaussian-splatting-e7d570081362)
- [Very good (technical) intro to 3D Gaussian Splatting](https://medium.com/@AriaLeeNotAriel/numbynum-3d-gaussian-splatting-for-real-time-radiance-field-rendering-kerbl-et-al-60c0b25e5544)
- [Gaussian Splatting is pretty cool](https://aras-p.info/blog/2023/09/05/Gaussian-Splatting-is-pretty-cool/)
- [Making Gaussian Splats smaller](https://aras-p.info/blog/2023/09/13/Making-Gaussian-Splats-smaller/)
- [Making Gaussian Splats more smaller](https://aras-p.info/blog/2023/09/27/Making-Gaussian-Splats-more-smaller/)
- [Compressing Gaussian Splats](https://blog.playcanvas.com/compressing-gaussian-splats/)
- [PlayCanvas Open Sources SOG](https://blog.playcanvas.com/playcanvas-open-sources-sog-format-for-gaussian-splatting/) - Spatially Ordered Gaussians, a super-compressed format based on WebP that is 15-20x smaller than PLY
- [Implementation Details](https://github.com/kwea123/gaussian_splatting_notes) - Technical deep dive
- [Mathematical Foundation](https://github.com/chiehwangs/3d-gaussian-theory) - Theory explanation
- [Mathematical details of forward and backward passes](https://github.com/joeyan/gaussian_splatting/blob/main/MATH.md)
- [PyTorch Implementation](https://myasincifci.github.io/) - Curated implementation of Vanilla 3DGS in PyTorch
- [NeRFs vs. 3DGS](https://edwardahn.me/writing/NeRFvs3DGS/)
- [Gaussian Head Avatars: A Summary](https://towardsdatascience.com/gaussian-head-avatars-a-summary-2bd17bd48500)
- [3D in Geospatial: NeRFs, Gaussian Splatting, and Spatial Computing](https://ckoziol.com/blog/2024/radiance_methods/)
- [Capture Guide](https://medium.com/@heyulei/capture-images-for-gaussian-splatting-81d081bbc826) - Image capture tutorial
- [Discussion about gs universal format](https://github.com/mkkellogg/GaussianSplats3D/issues/47#issuecomment-1801360116)

### Talks

- [Gaussian Splats: Ready for Standardization?](https://www.youtube.com/watch?v=0xdPpKSkO3I) - Metaverse Standards Forum 1/28/2025
- [Unity Integration Guide](https://www.youtube.com/watch?v=pM_HV2TU4rU&t=5298s) - Metaverse Standards Forum 5/6/2025

### Video Tutorials

- [Getting Started (Windows)](https://youtu.be/UXtuigy_wYc)
- [Two-Minute Explanation](https://youtu.be/HVv_IQKlafQ)
- [Computerphile 3DGS explanation](https://youtu.be/VkIJbpdTujE)
- [Gaussian Splats Town Hall - Part 2](https://youtu.be/5_GaPYBHqOo)
- [Intro to gaussian splatting (and Unity plugin)](https://www.xuanprada.com/blog/2023/10/22/intro-to-gaussian-splatting)
- [Jupyter Tutorial](https://www.youtube.com/watch?v=OcvA7fmiZYM)

### YouTube Channels

- [LichtFeld Studio](https://www.youtube.com/@LichtFeldStudio) - Tutorials, release walkthroughs and dev updates for [LichtFeld Studio](https://github.com/MrNeRF/LichtFeld-Studio)

## Credits

- Thanks to [Leonid Keselman](https://github.com/leonidk) for informing me about the release of the paper "Real-time Photorealistic Dynamic Scene Representation and Rendering with 4D Gaussian Splatting".
- Thanks to [Eric Haines](https://github.com/erich666) for suggesting the jupyter notebook viewer, windows tutorial and for fixing text hyphenations and other issues.
- Thanks to [Henry Pearce](https://github.com/henrypearce4D) for maintaining contributions.
- [Yehe Liu](https://x.com/YeheLiu)