| --- |
| license: cc-by-4.0 |
| pretty_name: GraspNet-Infinite object pool (Objaverse-LVIS, manipulation-reasonable subset) |
| task_categories: |
| - robotics |
| tags: |
| - 3d |
| - objaverse |
| - grasping |
| - synthetic-data |
| - scene-generation |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # GraspNet-Infinite object pool: 5,074 Objaverse-LVIS objects for tabletop scene generation |
|
|
| 5,074 rigid, closed, single-object 3D models (GLB with textures where the source had them) selected from |
| [Objaverse-LVIS](https://objaverse.allenai.org/) as **manipulation-reasonable tabletop objects** for a parallel-jaw gripper: |
| containers, bottles and packaging, tools, toys and figurines, personal and household items, food, hardware. |
| Every object carries a JSON record with its identity, licence and author, LVIS label, mesh statistics, native extent, |
| a typical real-world size and the scale factor to metres. The set is meant for composing multi-object tabletop scenes |
| (drop-in for BlenderProc, Isaac Sim, Kubric, PyBullet, trimesh/pyrender). |
|
|
| ## Layout |
|
|
| ``` |
| objects/A_containers_kitchenware.zip <lvis_category>/<uid>.glb + <lvis_category>/<uid>.json |
| objects/B_bottles_cans_packaging.zip |
| objects/C_tools_utensils.zip |
| objects/D_toys_figurines_animals.zip |
| objects/E_personal_office_household.zip |
| objects/F_food.zip |
| objects/G_hardware_parts.zip |
| manifest.csv / manifest.jsonl one record per object (same fields as the per-object JSON) |
| attribution.csv title, author, source URL, licence per object (keep with any redistribution) |
| load_example.py trimesh example: load, scale to metres, rest on a table |
| ``` |
|
|
| Unzip everything into one folder and the `file` field of each record is a relative path. |
|
|
| ## Per-object record |
|
|
| | field | meaning | |
| |---|---| |
| | `uid` | Objaverse / Sketchfab model id; `file` is `<lvis_category>/<uid>.glb` | |
| | `name`, `description`, `tags`, `author`, `author_url`, `source_url`, `published_at`, `licence` | Sketchfab metadata; licence is `CC-BY-4.0` or `CC0-1.0` (nothing else was admitted) | |
| | `lvis_category` | the LVIS label Objaverse-LVIS assigns (automatic; a few percent of labels are loose) | |
| | `family`, `family_letter` | our grouping: A containers & kitchenware, B bottles, cans & packaging, C tools & utensils, D toys, figurines & animals, E personal, office & household, F food, G hardware & parts | |
| | `shape_class` | `box`, `orb`, `cylinder` or `complex` (coarse, assigned per LVIS category) | |
| | `faces`, `components`, `watertight`, `textured`, `animated`, `bytes` | mesh statistics after texture-seam merging; `animated` means the GLB carries an animation (rest pose loads fine) | |
| | `native_extent`, `native_longest` | axis-aligned bounding-box extent in the GLB's own units (glTF units are nominally metres, but Objaverse scales are arbitrary) | |
| | `typical_longest_cm` | typical real-world longest dimension of this kind of object (per LVIS category, from our size table) | |
| | `scale_to_metres` | multiply vertex coordinates by this to bring the object to `typical_longest_cm` in metres: `(typical_longest_cm / 100) / native_longest` | |
| | `scale_source` | the size is a per-category prior, not a per-instance measurement; a per-object estimate is in progress | |
| | `size_note` | `small, kept for the size algorithm` marks categories under 4 cm (coins, beads, caps, berries) | |
| | `graspnet_nearest_object`, `graspnet_chamfer`, `graspnet_leakage_radius` | nearest GraspNet-1Billion object (id 0..87) under a scale-normalised, PCA-aligned Chamfer distance, and the radius below which objects were excluded as near-copies | |
|
|
| ## How the objects were selected |
|
|
| 1. **Label pass** over all 1,156 LVIS categories: kept the seven families above; removed vehicles, furniture, buildings, |
| appliances, people, plants, textiles and deformables, liquids, fixtures, weapons, flat slabs (plates, trays, books, |
| cards, phones, flatbreads), glass and eyewear, objects typically longer than 27 cm, and categories whose LVIS label does |
| not describe the contents (traffic cones filed as `cone`, barrels as `wine_bucket`, game characters as `mascot`). |
| Small objects were kept on purpose. Per-object name rules removed logos, lighting-catalogue uploads, barrels, |
| architecture, weapons under tool labels, NSFW; one object per uploader-and-mesh-count group (duplicates). |
| 2. **Licence**: CC-BY and CC0 only. |
| 3. **Mesh gates**: loads as at most 200 bodies, watertight after merging texture seams, at most three bodies, |
| 500 to 3,000,000 faces. |
| 4. **Benchmark leakage**: Chamfer distance to every GraspNet-1Billion object at least 0.01 (scale-normalised). |
|
|
| Not applied yet, so expect them in the set: label noise at the instance level (a few percent), rigged characters and |
| human figures (kept as figurines), untextured meshes (36% have no texture), arbitrary resting orientation |
| (use stable-pose computation or physics settling), and the per-category size prior (a mug record says 9 cm whether the |
| model is an espresso cup or a beer stein). |
|
|
| ## Loading |
|
|
| ```python |
| import json, trimesh |
| rec = json.loads(open("A_containers_kitchenware/mug/<uid>.json").read()) # after unzipping |
| m = trimesh.load(rec["file"], force="mesh") # merges the glTF scene into one mesh, keeps the texture |
| m.apply_scale(rec["scale_to_metres"]) # now metres at the typical size |
| m.apply_translation(-m.bounds[0] * [0, 0, 1]) # (example) rest on z = 0; glTF is y-up, so pick your table normal first |
| ``` |
|
|
| `load_example.py` does this for a few objects and prints their extents. For scene composition: scale to metres, let a |
| physics engine settle the objects on the table (or sample stable poses with `trimesh.poses.compute_stable_poses`), |
| render RGB-D with GraspNet-1Billion intrinsics. The `graspnet_*` fields let you keep or drop objects by similarity |
| to the benchmark. |
|
|
| ## Licence and attribution |
|
|
| Each model keeps its Sketchfab licence (`licence` field): CC-BY 4.0 requires attribution to the author; CC0 does not. |
| `attribution.csv` lists title, author, author URL, source URL and licence for every object; keep it with any |
| redistribution or publication. The Objaverse metadata is used under its ODC-By 1.0 licence. Please cite Objaverse: |
|
|
| ``` |
| @inproceedings{deitke2023objaverse, title={Objaverse: A Universe of Annotated 3D Objects}, |
| author={Deitke, Matt and Schwenk, Dustin and Salvador, Jordi and Weihs, Luca and Michel, Oscar and VanderBilt, Eli and |
| Schmidt, Ludwig and Ehsani, Kiana and Kembhavi, Aniruddha and Farhadi, Ali}, booktitle={CVPR}, year={2023}} |
| ``` |
|
|
| Selection, metadata and size table: Peize Li, 2026 (GraspNet-Infinite project). 5,074 objects, 20.5 GB zipped. |
| Family counts: A_containers_kitchenware 580, B_bottles_cans_packaging 317, C_tools_utensils 211, D_toys_figurines_animals 1809, E_personal_office_household 1062, F_food 1058, G_hardware_parts 37. |
|
|
| ## GraspNet-1Billion example scene |
|
|
| The folder `graspnet_example/` holds one complete GraspNet-1Billion scene (scene_0000, RealSense, all 256 views: RGB, depth, |
| labels, per-view object poses, camera trajectory) with its 9 object meshes and `reconstruct_scene.py`, a standalone script that |
| rebuilds the scene from the stored poses and checks it against the depth image. It is the reference layout for rendering |
| multi-object scenes in the GraspNet style. **That folder is CC BY-NC-SA 4.0** (GraspNet team, MVIG, SJTU), not CC-BY; see its README. |
|
|
