Ross ROSS = Recommend OSS · open-source software intelligence for agents

ziyc/drivestudio

A 3DGS framework for omni urban scene reconstruction and simulation. observed · 2026-08-28

github.com/ziyc/drivestudio · homepage · Python · MIT (permissive) 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

Full methodology

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

Member repositories

RepositoryRoleHealth v2
ziyc/drivestudiomain40

For agents

markdown · JSON · MCP: product_card(name="ziyc/drivestudio")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem