ziyc/drivestudio
A 3DGS framework for omni urban scene reconstruction and simulation. observed · 2026-08-28
Health v2 · maintenance only
40/100
- Activity 39
- Release rhythm 35
- Longevity 52
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 734
- days_rel: n/a
- days_push: 371
- n_releases_24m: 0
Adoption not part of the score
1254 stars · 157 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
DriveStudio is a Python framework for 3D Gaussian Splatting (3DGS) based reconstruction and simulation of dynamic urban driving scenes. It jointly reconstructs backgrounds, vehicles, and non-rigid actors like pedestrians and cyclists from driving logs, and supports major autonomous driving datasets including Waymo, NuScenes, KITTI, Argoverse2, PandaSet, and NuPlan.
Use cases
- reconstruct 3D urban driving scenes from lidar and camera logs
- simulate autonomous driving scenarios with dynamic actors
- train gaussian splatting models on Waymo or NuScenes datasets
- reconstruct pedestrians and cyclists in driving scenes
- generate novel view renders of street scenes for AV research
- benchmark neural scene reconstruction methods on driving datasets
When to choose
- you need high-fidelity reconstruction of full dynamic urban scenes including non-vehicle actors
- you work in autonomous driving simulation or AV perception research
- you want a unified codebase supporting multiple driving datasets and Gaussian representations
- you want the official OmniRe implementation for research reproduction
When to avoid
- you need real-time rendering on consumer hardware without a GPU
- your project involves indoor scenes or non-driving imagery
- you need a production-ready simulator with physics and sensor modeling rather than a research codebase
- you are not comfortable working with research-grade Python and large driving datasets
Facets
framework · maturity active
simulation computer-vision graphics machine-learning data-science autonomous-vehicles computer-vision simulation deep-learning robotics python cross-platform 3dgs gaussian-splatting urban-scene-reconstruction autonomous-driving neural-scene-graphs waymo nuscenes kitti argoverse pandaset nuplan research-code iclr-2025 omnire linux gpu
2 sources
- readme: https://github.com/ziyc/drivestudio · fetched 2026-08-28 · 8bd0d1999ad3
- homepage: https://ziyc.github.io/omnire/ · fetched 2026-08-29 · a90f6e14b692
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| ziyc/drivestudio | main | 40 |
For agents
markdown · JSON · MCP: product_card(name="ziyc/drivestudio")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem