AGILE: Hand-Object Interaction Reconstruction from Video via Agentic Generation
Paper • 2602.04672 • Published • 3
Dataset Viewer
The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code: FeaturesError
Exception: ArrowInvalid
Message: JSON parse error: Invalid value. in row 0
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 324, in _generate_tables
df = pandas_read_json(f)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
return pd.read_json(path_or_buf, **kwargs)
~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 815, in read_json
return json_reader.read()
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1014, in read
obj = self._get_object_parser(self.data)
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
obj = FrameParser(json, **kwargs).parse()
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1176, in parse
self._parse()
~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1391, in _parse
self.obj = DataFrame(
~~~~~~~~~^
ujson_loads(json, precise_float=self.precise_float), dtype=None
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/pandas/core/frame.py", line 782, in __init__
mgr = dict_to_mgr(data, index, columns, dtype=dtype, copy=copy, typ=manager)
File "/usr/local/lib/python3.14/site-packages/pandas/core/internals/construction.py", line 503, in dict_to_mgr
return arrays_to_mgr(arrays, columns, index, dtype=dtype, typ=typ, consolidate=copy)
File "/usr/local/lib/python3.14/site-packages/pandas/core/internals/construction.py", line 114, in arrays_to_mgr
index = _extract_index(arrays)
File "/usr/local/lib/python3.14/site-packages/pandas/core/internals/construction.py", line 677, in _extract_index
raise ValueError("All arrays must be of the same length")
ValueError: All arrays must be of the same length
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 244, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4523, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2768, in _head
return next(iter(self.iter(batch_size=n)))
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2972, in iter
for key, pa_table in ex_iterable.iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2483, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 327, in _generate_tables
raise e
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
pa_table = paj.read_json(
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
)
File "pyarrow/_json.pyx", line 364, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
return check_status(status)
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
AGILE Data
Prepared inputs and generated objects for AGILE: Hand-Object Interaction Reconstruction from Video via Agentic Generation.
HO3D inputs and generated assets for 18 sequences are available now. DexYCB configurations and prepared data will follow.
Download and use
From the AGILE code repository:
python tools/download_ho3d.py --scenes MC1 --output /ABS/data
Omit --scenes to download all released sequences. The downloader verifies archive and file checksums. Pass --revision COMMIT to pin a release.
The inputs are ready for optimization: they include RGB frames, hand/object masks, MoGe depth and camera intrinsics, WiLoR hand estimates and alignment, FoundationPose object poses, and the corresponding optimization mesh. You can skip preprocessing and object generation when using this release.
Use --data-root /ABS/data/HO3D/preprocessed when running optimization.
Files
| Path | Contents |
|---|---|
ho3d/preprocessed/SCENE.tar.gz |
All prepared inputs needed to load one sequence, including its 2D hand keypoints. |
ho3d/generated/SCENE.tar.gz |
Selected generated object mesh, material and texture. |
| Sequence inputs | Per-sequence file paths, frame coverage and contact frames. |
| Manifest | Archive inventory and SHA-256 checksums for every file. |
| SHA256SUMS | Archive checksums. |
Archives extract to:
HO3D/
preprocessed/train/SCENE/
generated/train/SCENE/object/
Each preprocessed archive is self-contained. Keep its camera data, hand estimates, object poses and optimization mesh together. The generated textured object is a separate appearance asset; use the prepared mesh associated with the object poses for optimization.
Coverage and versions
The release preserves the per-sequence input combinations used by the validated HO3D experiments. The latest packaging combines the former initialization files into each sequence's preprocessed archive; all extracted file paths and file contents are unchanged. The previous release remains available by revision.
Some prepared sequences end before the raw video; see the manifest for exact ranges. ABF12 includes extra depth-only files, while its RGB/mask observations stop at frame 1023. This data snapshot does not by itself establish exact paper metric reproduction.
Terms
HO3D-derived content remains subject to the original dataset terms. Obtain evaluation ground truth, MANO and external model weights separately under their respective terms; they are not included here. Load pickled research arrays only from trusted sources.
For AGILE's original contributions, the authors specify non-commercial research use; contact Professor Chunhua Shen for commercial use. No new permissive license is granted over third-party content.
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