Records
3
HF AUTHOR CLUSTER
spatialverse robotics datasets
3 robotics-tagged HF records from spatialverse, totaling 9,175 cumulative downloads. Some records cite published arxiv research.
DIRECT ANSWER
Author clusters consolidate every record from one publisher into a single buyer-review surface. spatialverse ships 3 robotics datasets on Hugging Face. Top license: cc-by-nc-4.0. Of those, 3 get a full standalone page, 0 get a shorter profile, and 0 are folded into this cluster.
Cumulative downloads
9,175
Top license
cc-by-nc-4.0
DATASETS
All 3 robotics records from spatialverse
3 of 3 datasets
SAGE-3D_InteriorGS_usdz
Published Dec 2025 · cc-by-nc-4.0 · spatialverse
SAGE-3D InteriorGS USDZ: USDZ-Format 3D Gaussian Scenes for Isaac Sim Paper | Project Page | Code InteriorGS dataset converted to USDZ format for seamless integration with NVIDIA Omniverse and Isaac Sim platforms.
- 5,400 downloads
- 86 likes
- n<1K
- Paper available
SAGE-3D_Collision_Mesh
Published Dec 2025 · cc-by-nc-4.0 · spatialverse
SAGE-3D Collision Mesh: Physics-Enabled Collision Bodies for 3D Gaussian Scenes Paper | Project Page | Code High-precision collision geometry dataset extracted from 1,000 indoor Mesh scenes, enabling physically accurate navigation and…
- 2,494 downloads
- 101 likes
- n<1K
- Paper available
SAGE-3D_VLN_Data
Published Dec 2025 · cc-by-4.0 · spatialverse
SAGE-3D VLN Data: Vision-Language Navigation Dataset with Hierarchical Instructions Paper | Project Page | Code A comprehensive VLN dataset featuring 2 million trajectory-instruction pairs across 1,000 indoor scenes, with hierarchical…
- 1,281 downloads
- 69 likes
- not specified
- Paper available
KEEP DIGGING
Use this record as part of a broader dataset review
A dataset record is only useful when it connects into the rest of the buyer workflow. The next review step is usually not another summary; it is a fit check, rights triage, source comparison, or custom bounty spec that names the missing proof.
For physical AI teams, the hard question is whether the public source can support a specific model objective under real deployment constraints. That requires adjacent dataset records, tools, comparisons, and sourcing paths, plus external references that a reviewer can open and challenge.
Use the links below to keep the review grounded. Start broad when discovery is incomplete, move into profile and comparison pages when the candidate source is known, and switch to custom collection when the blocker is rights, consent, geography, robot embodiment, or target environment coverage.
Where to go next
- Physical AI dataset catalogUse the catalog to compare source-backed dataset profiles by modality, task, rights signal, consent risk, and deployment fit.
- Hugging Face robotics indexScan the broader robotics dataset surface before narrowing into promoted profiles, comparisons, and custom collection specs.
- Dataset changelogTrack source updates, licensing notes, and buyer-readiness changes that should trigger a renewed review.
- Dataset fit checkerScore whether a public source is enough for the model, rights path, modalities, and target environment.
- License risk checkerSeparate source license language from contributor consent, redistribution, private-space risk, and model-use assumptions.
- Data spec generatorTurn a public-source gap into a scoped capture request with sample QA, metadata, and delivery requirements.
- Vendor alternatives hubCompare data providers when the answer is not another public dataset but a better sourcing or capture route.
- Data annotation companiesUse the company index to separate annotation vendors, data engines, marketplaces, and specialist capture teams.
Other places to verify the claims
- Scale AI physical AI data engineMarket context for why physical AI systems need custom, enriched, real-world data beyond generic labeling workflows.
- LeRobot documentationRobotics dataset and tooling context for Hugging Face based collection, sharing, conversion, and training workflows.
- Open X-EmbodimentA cross-embodiment robotics dataset reference for comparing trajectory scale, robot diversity, and VLA training assumptions.
- DROID datasetA large in-the-wild robot manipulation dataset reference for real-world trajectory capture and deployment transfer risk.
TRUELABEL ROUTING
Need data like spatialverse ships, but with cleaner rights?
If the Hub records don't carry the license, consent, or deployment fit your team needs, commission a custom collection on the same modality with explicit commercial terms.