# JonathonLuiten/Dynamic3DGaussians

Repository: https://github.com/JonathonLuiten/Dynamic3DGaussians
Canonical: https://ross.abutalabs.com/products/dynamic3dgaussians
Language: Python
License: NOASSERTION
License Family: other
Last push: 2023-12-22T06:49:05+00:00

## Health v2 (maintenance only)
Score: 28/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 79
- inputs: {"age_days": 1112, "days_push": 985, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2292, forks 149 (observed 2026-08-28T04:06:34.980059+00:00)

## What it is
Official PyTorch implementation of 'Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesis' (3DV 2024), which models dynamic 3D scenes as sets of 3D Gaussians that move and rotate over time. It extends Gaussian Splatting to dynamic scenes, enabling novel-view synthesis and dense 3D 6-DOF tracking, with training scripts and a custom visualizer.

## Use cases
- reconstruct dynamic 3D scenes from multi-camera video
- track objects in 3D with 6-DOF trajectories
- render novel views of dynamic scenes
- extend gaussian splatting to time-varying scenes
- visualize pretrained dynamic 3D gaussian models
- research codebase for dynamic scene representation

## When to choose
- you need dense 3D tracking plus novel-view synthesis for dynamic multi-view captures
- you want a clean, functional research codebase to build dynamic gaussian splatting on
- you have multi-camera video data and a CUDA GPU for training

## When to avoid
- you only need static scene reconstruction (original Gaussian Splatting suffices)
- you lack multi-view video data or GPU resources
- you need a production-ready, licensed product (license is non-standard)

## Facets
- artifact type: library
- maturity: maintenance
- function: computer-vision, graphics, machine-learning, simulation
- domain: computer-vision, graphics, deep-learning
- platform: python
- tags: gaussian-splatting, 3d-reconstruction, novel-view-synthesis, 6dof-tracking, dynamic-scenes, research-code, pytorch, 3dv-2024, linux, gpu, cuda

## Member repositories
- JonathonLuiten/Dynamic3DGaussians (main) score 28

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:34.980059+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 2026-08-30T02:40:39.590993+00:00, confidence not recorded.
  - readme: https://github.com/JonathonLuiten/Dynamic3DGaussians (fetched 2026-08-28T04:06:34.980059+00:00, sha 499bfb1e46f6)
- Data as of 2026-08-30T08:39:29.467469+00:00.