Caoza/PhysX-3D
PhysXNet & PhysXNet-XL This dataset aims to bridge the critical gap in physics-annotated 3D datasets. It is the first physics-grounded 3D dataset systematically annotated across five foundational dimensions: absolute scale, material, affordance, kinematics, and function description. Dataset Details ๐ Our paper has been accepted to NeurIPS 2025 (Spotlight) ๐ We have released the code for converting our JSON files to URDF at: urdf_gen.py.โฆ See the full description on the dataset page: https://huggingface.co/datasets/Caoza/PhysX-3D.
| Author / organization | Caoza |
|---|---|
| License (as declared) | gpl-3.0 |
| Downloads | 3.6K (as reported by Hugging Face) |
| Likes | 25 |
| Created | 8 July 2025 |
| Last updated at source | 11 November 2025 |
Popularity, last 3 days
3,592 now (+88 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Connected in the knowledge graph
- mradermacher/PhysX-Omni-GGUFModel ยท used to train
- mradermacher/PhysX-Omni-i1-GGUFModel ยท used to train
Recent changes
- 16 Oct 2026 Description: PhysXNet & PhysXNet-XL This dataset aims to bridge the critical gap in physics-annotated 3D datasets. It is the first physics-grounded 3D dataset systematically annotated across five foundational dimensions: absolute scale, material, afford โ PhysXNet & PhysXNet-XL This dataset aims to bridge the critical gap in physics-annotated 3D datasets. It is the first physics-grounded 3D dataset systematically annotated across five foundational dimensions: absolute scale, material, afford
Changes detected by Silytics between refreshes of the source.
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