HUGS Object Assets

This dataset provides the DGN_2k object assets used by HUGS: meshes and collision assets reprocessed with MeshProcess, scene configurations, original train/test splits, and rendered partial point clouds.

Release status: complete. Both archives have been uploaded and their remote SHA-256 metadata matches the locally verified files. The archive content is available at dataset revision b6df8d4721a05a73f657afd15d935da081a3e1e5.

These are locally reprocessed assets, not a byte-identical mirror of JiayiChenPKU/BODex. Raw mesh sources are available from that upstream dataset and are not redistributed in this release.

Repository layout

object_assets/
├── checksums.sha256
└── DGN_2k/
    ├── DGN_2k_processed_scene_cfg_valid_split.tar.gz
    └── DGN_2k_three_realsense_d435_random4096.tar.gz

The first archive contains processed_data/, scene_cfg/, and valid_split/. The second contains vision_data/three_realsense_d435_random4096/. Neither archive contains an outer DGN_2k/ directory. Both must be extracted into the same object_assets/DGN_2k/ destination.

The existing mesh, NPY, and JSON files, object/scene IDs, scales, splits, and directory relationships are preserved. This release does not include raw meshes, single-view-only vision directories, logs, backups, grasps, Human Prior data, or checkpoints.

Download and extract

From a directory where the downloaded repository will be stored:

hf download MingruiYu/HUGS --repo-type dataset --local-dir HUGS
cd HUGS
(cd object_assets && sha256sum -c checksums.sha256) &&
mkdir -p object_assets/DGN_2k &&
tar -xzf object_assets/DGN_2k/DGN_2k_processed_scene_cfg_valid_split.tar.gz \
  -C object_assets/DGN_2k &&
tar -xzf object_assets/DGN_2k/DGN_2k_three_realsense_d435_random4096.tar.gz \
  -C object_assets/DGN_2k

The resulting data layout is:

object_assets/DGN_2k/
├── processed_data/<object_id>/
│   ├── mesh/
│   ├── urdf/
│   │   ├── coacd.urdf
│   │   ├── coacd.xml
│   │   └── meshes/
│   ├── info/
│   └── complete_point_cloud.npy
├── scene_cfg/<object_id>/
│   ├── floating/*.npy
│   └── tabletop_ur10e/*.npy
├── valid_split/
│   ├── all.json
│   ├── train.json
│   └── test.json
└── vision_data/three_realsense_d435_random4096/
    ├── cam_in.npy
    └── <object_id>/<scene_type>/<scene_stem>/
        ├── partial_pc_00.npy ... partial_pc_03.npy
        └── cam_ex_00.npy ... cam_ex_03.npy

Only the first archive is required for workflows that consume scene configurations and complete object point clouds. Download the second archive for partial point clouds. The checksum command above assumes both archives are present.

For existing AnyScaleGrasp consumers, use ${ANYSCALEGRASP_DATA_ROOT}/object/DGN_2k as the extraction destination instead: create that directory, then replace both -C arguments with that full path. Extracting into object/ would be incorrect for these archives. No --strip-components option is needed.

Contents and coverage

Sizes below are uncompressed decimal bytes.

Component	Files	Bytes
processed_data/	76,688	2,455,769,539
scene_cfg/	185,088	260,923,296
valid_split/	3	209,144
vision_data/three_realsense_d435_random4096/	1,480,705	16,273,005,574
Total	1,742,484	18,989,907,553

• processed_data/ includes 2,397 object directories, including partially processed objects. Not every directory has every output shown above.
• The original valid split contains 2,331 objects: 1,864 train and 467 test, with no overlap.
• Scene configurations exist for 2,323 objects. Eight objects in the split have no scene configurations (six train, two test). Splits and incomplete directories are preserved, not silently filtered or repaired.
• There are 185,088 scenes: 27,876 floating and 157,212 tabletop.
• Each scene has four partial point clouds and four extrinsic files, totaling 740,352 clouds and 740,352 extrinsic files, plus the shared cam_in.npy.

Data conventions

Item	Convention
Scale anchors	0.020, 0.028, 0.042, 0.060, 0.081, 0.106, 0.133, 0.162, 0.194, 0.227, 0.263, 0.300
Scale source	Read the actual scale array inside the scene NPY dictionary. A filename containing scale008 can represent 0.081.
Scene pose	Translation in meters, quaternion order WXYZ. Mesh/XML/URDF/info paths are resolved relative to the scene file's parent directory.
Complete point clouds	Sampled files have shape (4096, 3), float16, in normalized object coordinates. Apply the scene scale and pose for world coordinates.
Partial point clouds	Float16 XYZ points in scene world coordinates. 4096 is an upper bound; some clouds contain fewer points.
Three-view directory	Tabletop samples fuse three camera views; floating samples remain single-view. Four samples are stored per scene.
Extrinsics	Sampled floating matrices have shape (4, 4) and tabletop matrices (3, 4, 4), float32. MeshProcess uses row-vector camera-to-world transforms.
cam_in.npy	A 4×4 row-vector OpenGL projection matrix, not a conventional 3×3 intrinsic matrix.
Scene NPY	Serialized dictionaries loaded with numpy.load(path, allow_pickle=True).item(). Load pickle-containing files only from a trusted release.

The checked-in renderer configuration uses 1280×720 images, fx=910.944763183594, fy=910.721984863281, cx=642.13818359375, cy=367.6796875, near plane 0.1 and far plane 10.0. These values are consistent with the released cam_in.npy; the complete historical generation environment has not been recovered.

Provenance and limitations

Local processing logs dated May 13, 2026 record full MeshProcess processing; the selected rendering log is dated May 20, 2026. A previous comparison of eight simplified meshes against a local BODex backup found different SHA-256 hashes. The upstream dataset link therefore documents provenance, not a substitute for these exact reprocessed assets.

The MeshProcess checkout inspected for format interpretation was 022b41f2ebb32b3de3ea78b2723f180eaef2118e. This is an inspection reference, not a confirmed historical generating commit. Historical seeds and the complete producer environment remain unconfirmed. No full numerical quality audit or simulation benchmark is claimed.

Archive verification

Archive	Compressed bytes	SHA-256
DGN_2k_processed_scene_cfg_valid_split.tar.gz	872,815,299	32204e6557ca2c7f35b01f05633341b4d226f475502b19c6742a98d63d66d63e
DGN_2k_three_realsense_d435_random4096.tar.gz	14,386,467,307	bf658b10af71ceeb0d32d43126940da9415e607917e47b22eacf5d0fb00d5db5

Both archives were compared against all source files with GNU tar, and their member paths, file counts, and uncompressed sizes were checked. Selected files were extracted into a fresh DGN_2k directory; split sets, two scene configurations, relative mesh/XML/URDF/info references, complete/partial point clouds, and camera matrices passed a loading smoke check. This does not constitute a full numerical quality audit or a physics/simulation benchmark.

Attribution and license

Source dataset: JiayiChenPKU/BODex, inspected revision 7f25e59b111ef3405aea242199ec3e07f2965c13. Its dataset card declares CC BY-NC 4.0. This derived release retains that noncommercial license declaration and upstream attribution. Original mesh-source terms continue to apply where applicable; see THIRD_PARTY_NOTICES.md.

Please cite the upstream work when using these assets:

BODex: Scalable and Efficient Robotic Dexterous Grasp Synthesis Using Bilevel Optimization. ICRA 2025. arXiv:2412.16490.

Upstream project and MeshProcess code.