# yzslab/gaussian-splatting-lightning

A 3D Gaussian Splatting framework with various derived algorithms and an interactive web viewer

Repository: https://github.com/yzslab/gaussian-splatting-lightning
Canonical: https://ross.abutalabs.com/products/gaussian-splatting-lightning
Language: Jupyter Notebook
License: NOASSERTION
License Family: other
Last push: 2026-05-25T13:10:03+00:00

## Health v2 (maintenance only)
Score: 58/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 84, release rhythm 16, longevity 75
- inputs: {"age_days": 1062, "days_push": 100, "days_rel": 518, "gap_med": 94.0, "n_releases_24m": 3}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1101, forks 85 (observed 2026-08-28T04:03:35.716806+00:00)

## What it is
A PyTorch Lightning implementation of 3D Gaussian Splatting with many derived algorithms (Mip-Splatting, LightGaussian, 2DGS, deformable Gaussians, etc.) and an interactive web viewer. It supports multi-GPU training, multiple dataset formats, and video rendering.

## Use cases
- train 3d gaussian splatting models from colmap captures
- reconstruct 3d scenes from photos with multi-gpu training
- view and edit gaussian splatting models in a browser
- render camera path videos from trained splat models
- try research variants like mip-splatting or 2dgs
- segment or deform gaussian splat scenes

## When to choose
- you want a maintained, feature-rich 3DGS training framework with many derived algorithms
- you need multi-GPU/node training or large image datasets without OOM
- you want an interactive web viewer and scene editor for splat models

## When to avoid
- you need a simple one-command pipeline with minimal configuration
- you require a permissive license (license is non-standard)
- you work outside Python/PyTorch ecosystems

## Facets
- artifact type: library
- maturity: active
- function: machine-learning, deep-learning, graphics, simulation, data-visualization
- domain: computer-vision, graphics, machine-learning, deep-learning
- platform: python, cross-platform
- tags: gaussian-splatting, pytorch-lightning, neural-rendering, 3d-reconstruction, nerf, web-viewer, multi-gpu, gpu, linux

## Member repositories
- yzslab/gaussian-splatting-lightning (main) score 58

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:35.716806+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:45:45.120598+00:00, confidence not recorded.
  - readme: https://github.com/yzslab/gaussian-splatting-lightning (fetched 2026-08-28T04:03:35.716806+00:00, sha c27c3a9a1867)
- Data as of 2026-08-30T08:39:29.467469+00:00.