The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ArrowInvalid
Message: JSON parse error: The document is empty.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 280, in _generate_tables
df = pandas_read_json(f)
^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 34, in pandas_read_json
return pd.read_json(path_or_buf, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 815, in read_json
return json_reader.read()
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1014, in read
obj = self._get_object_parser(self.data)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
obj = FrameParser(json, **kwargs).parse()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1176, in parse
self._parse()
File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1391, in _parse
self.obj = DataFrame(
^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/core/frame.py", line 778, in __init__
mgr = dict_to_mgr(data, index, columns, dtype=dtype, copy=copy, typ=manager)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/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/python3.12/site-packages/pandas/core/internals/construction.py", line 114, in arrays_to_mgr
index = _extract_index(arrays)
^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/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/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 283, in _generate_tables
raise e
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 246, in _generate_tables
pa_table = paj.read_json(
^^^^^^^^^^^^^^
File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: JSON parse error: The document is empty.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
MisCue3D
MisCue3D is a diagnostic dataset for studying context dependence in visually grounded 3D pose estimation. The dataset is designed to test whether a model's predicted pose, depth, or scale changes when the target object itself is held fixed but the surrounding visual context is changed.
This repository contains rendered observations and metadata from controlled Unreal Engine experiments. It does not contain Unreal Engine project files, .uasset files, source meshes, source textures, or marketplace/source 3D assets.
The dataset is intended for diagnostic evaluation.
Context families
MisCue3D contains three controlled context families.
1. Scale referent
A familiar referent object is rendered near the target object. The referent object's scale is varied while the target object and camera are held fixed.
Conditions include:
1x: normal referent scale0.5x: smaller referent scale2x: larger referent scale
2. Support plausibility
The target object is rendered either with a plausible support surface or without support.
Conditions include:
with_support: target has a plausible support contextwithout_support: target appears unsupported or floating
3. Insertion vs. no-container
An elongated target object is rendered either inserted into a container that occludes part of it, or rendered alone with the same target pose.
Conditions include:
with_container: target is inserted into a containerwithout_container: container is removed while the target pose is preserved
Repository structure
This repository contains:
Insertion_no_container/
Rendered examples and metadata for the insertion versus no-container context family.NYC_East_Village_floating_object/
Rendered examples and metadata for the support plausibility context family.NYC_East_Village_scale_referent/
Rendered examples and metadata for the scale-referent context family.summary.json
Dataset-level summary file.insertion_no_container_sampled_by_us_object_paths_params.csv
Sampled object/path parameter file for the insertion/no-container family.data_manifest.jsonl
File-level manifest listing rendered image files and their relative paths.
Rendered file types
The dataset may contain the following rendered image types:
lit.png
RGB rendered image.seg.png
Segmentation image.normal.png
Surface-normal rendering.
The exact directory layout follows the context family, camera, and condition structure used during data generation.
What is included
This repository includes:
- rendered RGB images
- segmentation renderings
- normal renderings
- metadata files
- file manifests
- condition labels and experiment organization files
What is not included
This repository does not redistribute:
- Unreal Engine project files
- Unreal Engine map/source scene files
.uassetfiles- raw 3D meshes
- raw textures or materials
- marketplace/source 3D assets
The released files are rendered outputs and metadata only.
Intended use
MisCue3D is intended for research on:
- 3D pose estimation
- visually grounded 3D reconstruction
- context dependence in single-image 3D models
- robustness and diagnostic evaluation
- controlled evaluation of pose, depth, and scale predictions
It is not intended as a general-purpose object recognition dataset or a source asset repository.
Limitations
MisCue3D is synthetic and generated from controlled rendering experiments. Its context families are designed to isolate specific visual cues, so the distribution is intentionally diagnostic rather than naturally sampled. Results on MisCue3D should therefore be interpreted as evidence of controlled context sensitivity, not as a direct estimate of real-world deployment performance.
The dataset reflects the selected object categories, rendered environments, camera configurations, and context interventions used during generation. Models may behave differently under other rendering engines, object distributions, lighting conditions, or real-image data.
License
Rendered images, annotations, metadata, and manifest files in this repository are released under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
Third-party source assets, Unreal Engine project files, raw meshes, raw textures, materials, and marketplace/source assets are not redistributed in this repository and remain subject to their original licenses.
Citation
Citation information will be added after the associated anonymous submission is de-anonymized.
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