DatasetFeatured
HM3D
Habitat-Matterport 3D — large-scale realistic indoor scans for navigation research.
DatasetFeatured
ScanNet
RGB-D indoor scene dataset with reconstructions and semantics — backbone for 3D perception.
Why: Core RGB-D scene understanding dataset
Overview
ScanNet is catalogued on Embodied AI Hub as a curated dataset for embodied AI builders.
RGB-D indoor scene dataset with reconstructions and semantics — backbone for 3D perception.
Why it matters: Core RGB-D scene understanding dataset
Use the official repository and docs as the source of truth for install pins, licenses, and hardware requirements.
Who it is for
Researchers, students, and builders comparing open embodied stacks.
Key highlights
- RGB-D indoor scene dataset with reconstructions and semantics — backbone for 3D perception.
- Type: dataset; categories: dataset
- Marked recommended on the hub
When to use
- You are mapping the open embodied AI landscape
- You need a starting URL and judgment note before deep-diving
When not to use
- You need production SLAs or certified industrial support only
- License or hardware constraints are incompatible with your deployment
Getting started
- 1Open the official URL and read README install pins.
- 2Skim license and citation requirements.
- 3Run the smallest official example before scaling experiments.
- 4Cross-link related hub resources (sim / data / policy) for a full stack.
Papers & reading
Caveats & pitfalls
- Hub cards are curated summaries — always verify upstream docs.
- Stars and dates drift; treat extra.stars as approximate.
Content reviewed 2026-07-28