--- pretty_name: UniPhys-Bench license: cc-by-nc-4.0 language: - en tags: - 3d - physical-grounding - articulation - robotics - simulation - benchmark size_categories: - 1K+ 454 in Part 2 | Across both releases | Across both releases | ## Dataset showcase The following benchmark-level examples visualize 3D assets and selected physical-grounding results across the complete UniPhys-Bench. Each row follows one articulated object from its original textured mesh through part decomposition and affordance grounding to the motion of all articulated parts. In the affordance view, **redder parts indicate higher interactivity**. | Original Mesh | Part Decomposition | Affordance | Articulated Motion | | :---: | :---: | :---: | :---: | | Raw textured geometry | Part-level segmentation |

**Redder = more interactive** | All articulated parts in motion | | Example 1 original mesh

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| ## Release scope | Statistic | Value | | --- | ---: | | Articulated objects in this repository | 1,473 | | Entity ID range | `UPB_00000454`–`UPB_00001926` | | Role | Primary release | The complete benchmark used in the paper contains 1,927 articulated 3D objects and is hosted as two independent releases: | Release | Contents | Objects | Entity IDs | | --- | --- | ---: | --- | | [UniPhys-Bench](https://huggingface.co/datasets/spatialverse/UniPhys-Bench) | Manycore-provided assets | 1,473 | `UPB_00000454`–`UPB_00001926` | | [UniPhys-Bench Part 2](https://huggingface.co/datasets/breezexian/UniPhys-Bench-Part2) | Evaluation-only assets held out from the UniPhys-40K source distribution | 454 | `UPB_00000000`–`UPB_00000453` | The two releases use the same annotation schema and evaluation protocol. They are hosted separately so that each repository can state the provenance and terms applicable to the assets it contains. Entity IDs are globally unique across the two releases and should not be renumbered. The benchmark covers diverse object categories, structural complexities, part granularities, modeling styles, scales, masses, materials, and articulation patterns. ## Benchmark construction The assets in this repository were provided by Manycore Tech, and their part decompositions were created by professional designers. The UniPhys pipeline first produces articulation and physical-property annotations. Human annotators then inspect and correct joint type, axis, pivot, motion range, motion-dependent part groupings, and intrinsic physical-property plausibility for motion-relevant components. UniPhys-Bench Part 2 provides the complementary source-distribution split used by the complete benchmark. It is distributed separately and is not contained in this repository. ## Annotation scope | Task | Inputs | Ground truth | | --- | --- | --- | | Part-level intrinsic physical grounding | object and target-part geometry | part identity, semantic descriptions, material, density, Young's modulus, hardness, Poisson's ratio, friction, graspability, and affordance | | Kinematic parameter grounding | object and target-part geometry | prismatic/revolute joint type, axis, pivot, and motion range | | Articulation structure grounding | object and target-part geometry plus candidate-part metadata | IDs of parts that move together with the target part | | Object-level physical grounding | complete-object geometry | object identity, category, dimensions, and mass | Part-property units follow the paper: density is in `g/cm^3`, Young's modulus in `GPa`, hardness in `HV`, and Poisson's ratio and friction are unitless. Object dimensions are `[L, W, H]` in centimeters and mass is in kilograms. Affordance is scored from 1 to 10, with smaller values indicating higher affordance. Motion labels use `B` for prismatic translation and `C` for revolute rotation. The broader part-level annotations additionally use `A` for contact-only and `D` for rigid or fixed parts. ## Dataset structure Each benchmark object is stored in one `UPB_` directory. For example: ```text UPB_00000454/ ├── annotations/ │ ├── object.json │ ├── part_1.json │ ├── part_2.json │ └── ... ├── full_model/ │ ├── model.obj │ ├── material.mtl │ └── texture files ├── meta_data.json ├── model.urdf ├── parts/ │ ├── part_1.obj │ ├── part_2.obj │ ├── material and texture files │ └── ... └── plys/ ├── model.ply ├── 1.ply ├── 2.ply └── ... ``` | Path | Description | | --- | --- | | `parts/part_.obj` | Decomposed part mesh, with its available MTL and texture assets. | | `full_model/model.obj` | Complete object OBJ produced by concatenating all released part meshes. | | `plys/model.ply` | Point cloud for the complete object. | | `plys/.ply` | Part point cloud aligned with `parts/part_.obj`. | | `annotations/object.json` | Object identity, category, real-world dimensions, and mass. | | `annotations/part_.json` | Part semantics, intrinsic physical properties, articulation parameters, and dependency group. | | `meta_data.json` | Entity provenance, object summary, geometry metadata, and annotation version. | | `model.urdf` | Articulated assembly of all released parts using the annotated joints and motion parameters. | The same numeric part ID is used by `part_.obj`, `.ply`, and `part_.json`, so geometry and annotations can be joined without an additional mapping file. ### Simulation-ready URDF `model.urdf` assembles all parts and encodes the annotated joint types and motion parameters. During export, the mesh is rescaled using the annotated object dimensions so that the assembled asset has a real physical size. URDF geometry uses **meters**, while `annotations/object.json` stores dimensions in centimeters. > [!IMPORTANT] > The released URDF provides the articulated geometry and kinematic assembly, > but intrinsic physical properties are not written into the URDF. Density, > friction, mass, and other physical values should be read from the JSON > annotations and assigned as needed for the target simulator and experiment. ### Metadata `meta_data.json` stores the dataset origin and released entity summary. A Manycore entity uses metadata of the following form: ```json { "id": "UPB_00000454", "source": [ { "dataset": "UniPhys-Bench", "organization": "Manycore Tech Inc.", "license_ref": "UniPhys-Bench" } ], "object": { "category": "Furniture/StorageFurniture", "object_name": "Corner Display Cabinet with Drawer" }, "geometry": { "asset_type": "decomposed_parts", "num_parts": 6, "format": "obj" }, "annotation": { "version": "v1.0" } } ``` ### Part-level annotations Each `annotations/part_.json` contains the part description, intrinsic physical properties, motion type, joint parameters, and motion dependency: ```json { "index": { "type_name": "default", "entity": "UPB_00000000", "label": "3" }, "part_level": { "part_name": "Front Seat Trim Bar", "affordance": 2, "graspable": false, "basic_description": "Slim ABS trim piece at the front edge of the seat.", "functional_description": "Covers a seam and provides a finished edge.", "movement_description": "Revolute; attached to the seat base.", "grasp_description": "Grasp the handle of the bar." }, "basic_info": { "material": "metal/Steel", "density": 7.85, "young": 200.0, "hardness": 180.0, "poisson": 0.3, "friction": 0.45 }, "kinematic_info": { "motion_types": ["C"], "motion_info": { "dependency": [3], "C": { "axis": [-1.0, 0.0, 0.0], "pos": [-0.02277967, 0.38144422, -0.02326505], "range": [0.0, 0.785], "damping": 0.03 } } } } ``` `kinematic_info.motion_info.dependency` lists the part IDs that move together. For movable parts, `B` contains prismatic parameters and `C` contains revolute parameters; `axis`, `pos`, `range`, and `damping` describe the corresponding joint. `range` is the `[lower, upper]` motion interval; for a revolute (`C`) joint, both limits are rotation angles expressed in radians. ### Object-level annotations `annotations/object.json` contains the object identity and global physical properties: ```json { "object_name": "Example Object", "category": "Furniture/StorageFurniture", "volume": [70.0, 68.0, 110.0], "mass": 15.5 } ``` `volume` is `[length, width, height]` in centimeters and `mass` is in kilograms. The values above illustrate the schema; released files contain the verified values for each entity. ## Download and prepare Download this primary release: ```bash hf download \ spatialverse/UniPhys-Bench \ --repo-type dataset \ --local-dir data/UniPhys-Bench ``` Generate model-ready point clouds: ```bash python pre_process/generate_npzs.py \ --data_root data/UniPhys-Bench \ --output_dir data/UniPhys-Bench-processed/npzs ``` Generate one inference manifest for each evaluation task: ```bash python pre_process/generate_jsons_for_inference.py \ --data_root data/UniPhys-Bench \ --npz_dir data/UniPhys-Bench-processed/npzs \ --output_dir data/UniPhys-Bench-processed/manifests ``` The command writes: ```text manifests/ ├── intrinsic_physics_part.json ├── intrinsic_physics_object.json ├── kinematic_parameters.json └── articulation_structure.json ``` Each sample keeps its complete benchmark annotation. UniPhysGen inference embeds that record as `source_sample`, which the evaluation package reads as ground truth. To reproduce results on the complete benchmark of 1,927 articulated objects, also download [UniPhys-Bench Part 2](https://huggingface.co/datasets/breezexian/UniPhys-Bench-Part2) and evaluate both releases with the same protocol. Keep the original entity IDs when preparing a combined data root. ## Evaluation protocol The paper reports the following metrics: | Category | Metrics | | --- | --- | | Kinematic parameters | joint-type accuracy, axis angular error in degrees, pivot-to-ground-truth-axis distance, and motion-range mIoU | | Articulation structure | set mIoU and micro-F1 over motion-coupled part IDs | | Material properties | material-category accuracy, density ALDE, and friction MAE | | Object scale and mass | ALDE and MnRE for dimensions and mass | | Affordance | MAE over the 1-10 affordance score | Kinematic parameters are evaluated on ground-truth movable parts, separating parameter estimation from movable-part identification. Axis directions `a` and `-a` are treated as the same articulation axis. Pivot error is measured in a shared AABB-normalized object frame as point-to-ground-truth-axis distance. Motion ranges are canonicalized to unsigned intervals before computing IoU. Run the four evaluators on prediction JSON files or directories of per-sample records: ```bash python -m eval intrinsic_physics_part PREDICTIONS \ --output intrinsic_physics_part_metrics.json python -m eval intrinsic_physics_object PREDICTIONS \ --output intrinsic_physics_object_metrics.json python -m eval kinematic_parameters PREDICTIONS \ --output kinematic_parameters_metrics.json python -m eval articulation_structure PREDICTIONS \ --output articulation_structure_metrics.json ``` See the [UniPhysGen README](https://github.com/breezexian/UniPhysGen#reproducing-uniphys-bench-results) for the complete inference workflow and checkpoint commands. ## Intended use UniPhys-Bench is intended for research evaluation of unified physical grounding, including articulation reasoning, physical-property estimation, simulation-ready asset construction, embodied AI, and robotics simulation. It is an evaluation benchmark and should not be mixed into UniPhysGen training or model-selection data. ## Scope and usage considerations - Human annotators verify and correct articulation annotations and assess physical-property plausibility to support consistent research evaluation. Physical values are reference estimates for the depicted objects. - The benchmark cannot cover every object category, material, mechanism, part granularity, or mesh failure mode. - Results can depend on geometric completeness, scale correctness, texture quality, and candidate part decomposition. ## Licensing and provenance The complete contents of this release—including assets, annotations, metadata, derived representations, and dataset organization—are licensed under [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/). Commercial use is not permitted. See [LICENSE_UNIPHYS_BENCH](https://huggingface.co/datasets/spatialverse/UniPhys-Bench/blob/main/LICENSE_UNIPHYS_BENCH) for the release-specific license notice and attribution information. Use the `source` field in each entity's `meta_data.json` to retain the supplied organization and license reference. Retain all required attribution, license, and modification notices when sharing the data. ## Citation ```bibtex @article{li2026uniphysgen, title = {UniPhysGen: Unified Physical Grounding for Simulation-Ready 3D Assets}, author = {Li, Xian and Wei, Rong and Yang, Lujie and Huang, Haolin and Fang, Junyuan and Tang, Siliang and Xiao, Jun and Tang, Rui and Li, Juncheng}, journal = {arXiv preprint arXiv:2607.13586}, year = {2026} } ```