Datasets:

PoopBear
/

3D-IDE-data

License:

Dataset Viewer

Split (3)

train

The dataset viewer is not available for this split.

Cannot load the dataset split (in streaming mode) to extract the first rows.

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
info: struct<description: string, url: string, version: string, year: int64, contributor: string, date_cre (... 19 chars omitted)
  child 0, description: string
  child 1, url: string
  child 2, version: string
  child 3, year: int64
  child 4, contributor: string
  child 5, date_created: timestamp[s]
license: struct<url: string, name: string>
  child 0, url: string
  child 1, name: string
data_type: string
data_subtype: string
annotations: list<item: struct<scene_id: string, question_type: string, answer_type: string, question_id: int64,  (... 205 chars omitted)
  child 0, item: struct<scene_id: string, question_type: string, answer_type: string, question_id: int64, answers: li (... 193 chars omitted)
      child 0, scene_id: string
      child 1, question_type: string
      child 2, answer_type: string
      child 3, question_id: int64
      child 4, answers: list<item: struct<answer: string, answer_confidence: string, answer_id: int64>>
          child 0, item: struct<answer: string, answer_confidence: string, answer_id: int64>
              child 0, answer: string
              child 1, answer_confidence: string
              child 2, answer_id: int64
      child 5, rotation: struct<_x: int64, _y: int64, _z: double, _w: double>
          child 0, _x: int64
          child 1, _y: int64
          child 2, _z: double
          child 3, _w: double
      child 6, position: struct<x: double, y: double, z: double>
          child 0, x: double
          child 1, y: double
          child 2, z: double
questions: list<item: struct<scene_id: string, situation: string, alternative_situation: list<item: string>, qu (... 36 chars omitted)
  child 0, item: struct<scene_id: string, situation: string, alternative_situation: list<item: string>, question: str (... 24 chars omitted)
      child 0, scene_id: string
      child 1, situation: string
      child 2, alternative_situation: list<item: string>
          child 0, item: string
      child 3, question: string
      child 4, question_id: int64
task_type: string
to
{'info': {'description': Value('string'), 'url': Value('string'), 'version': Value('string'), 'year': Value('int64'), 'contributor': Value('string'), 'date_created': Value('timestamp[s]')}, 'license': {'url': Value('string'), 'name': Value('string')}, 'data_type': Value('string'), 'data_subtype': Value('string'), 'task_type': Value('string'), 'questions': List({'scene_id': Value('string'), 'situation': Value('string'), 'alternative_situation': List(Value('string')), 'question': Value('string'), 'question_id': Value('int64')})}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, 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 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 478, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2815, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2352, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2377, 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 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 419, 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 310, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 130, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              info: struct<description: string, url: string, version: string, year: int64, contributor: string, date_cre (... 19 chars omitted)
                child 0, description: string
                child 1, url: string
                child 2, version: string
                child 3, year: int64
                child 4, contributor: string
                child 5, date_created: timestamp[s]
              license: struct<url: string, name: string>
                child 0, url: string
                child 1, name: string
              data_type: string
              data_subtype: string
              annotations: list<item: struct<scene_id: string, question_type: string, answer_type: string, question_id: int64,  (... 205 chars omitted)
                child 0, item: struct<scene_id: string, question_type: string, answer_type: string, question_id: int64, answers: li (... 193 chars omitted)
                    child 0, scene_id: string
                    child 1, question_type: string
                    child 2, answer_type: string
                    child 3, question_id: int64
                    child 4, answers: list<item: struct<answer: string, answer_confidence: string, answer_id: int64>>
                        child 0, item: struct<answer: string, answer_confidence: string, answer_id: int64>
                            child 0, answer: string
                            child 1, answer_confidence: string
                            child 2, answer_id: int64
                    child 5, rotation: struct<_x: int64, _y: int64, _z: double, _w: double>
                        child 0, _x: int64
                        child 1, _y: int64
                        child 2, _z: double
                        child 3, _w: double
                    child 6, position: struct<x: double, y: double, z: double>
                        child 0, x: double
                        child 1, y: double
                        child 2, z: double
              questions: list<item: struct<scene_id: string, situation: string, alternative_situation: list<item: string>, qu (... 36 chars omitted)
                child 0, item: struct<scene_id: string, situation: string, alternative_situation: list<item: string>, question: str (... 24 chars omitted)
                    child 0, scene_id: string
                    child 1, situation: string
                    child 2, alternative_situation: list<item: string>
                        child 0, item: string
                    child 3, question: string
                    child 4, question_id: int64
              task_type: string
              to
              {'info': {'description': Value('string'), 'url': Value('string'), 'version': Value('string'), 'year': Value('int64'), 'contributor': Value('string'), 'date_created': Value('timestamp[s]')}, 'license': {'url': Value('string'), 'name': Value('string')}, 'data_type': Value('string'), 'data_subtype': Value('string'), 'task_type': Value('string'), 'questions': List({'scene_id': Value('string'), 'situation': Value('string'), 'alternative_situation': List(Value('string')), 'question': Value('string'), 'question_id': Value('int64')})}
              because column names don't match

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3D-IDE Training Data

Complete, verified training data for 3D-IDE (CVPR 2026). This is the exact data used in our experiments — byte-identical to our training server. Use md5_manifest.txt / md5_manifest_scannet.txt to verify your local copy without re-downloading.

ScanNet notice: scannet/ archives and parts of the metadata are derived from ScanNet. By downloading them you agree to the ScanNet Terms of Use.

File	Size	Contents (archive-internal paths)	Extract into
`3d_ide_data.zip`	4.3 GB	`processed/`, `metadata/`, `benchmark/`, `balanced/`, `embodiedscan/`, `multi.yaml`	`data/`
`scannet/scannet_posed_images_part1.zip`	~25 GB	`posed_images/scene0000_00 …` (first half)	`data/scannet/`
`scannet/scannet_posed_images_part2.zip`	~25 GB	`posed_images/…` (second half)	`data/scannet/`
`scannet/scannet_mask_pcd.zip`	~10 GB	`mask/`, `pcd_with_object_aabbs/`	`data/scannet/`
`vggt_features/vggt_features_part{1..9}.zip`	9 × ~43 GB	`scene…/vggt_sliced.npy` (no wrapper dir!)	`data/scannet/posed_images_3d_feature_vggt/`
`md5_manifest.txt`	—	MD5 of every file in `3d_ide_data.zip`	—
`md5_manifest_scannet.txt`	—	MD5 of every raw file under `scannet/`	—

The loose processed/, metadata/, benchmark/, balanced/ folders in this repo mirror the contents of 3d_ide_data.zip for convenient single-file access.

Extraction

Run from the repo root of 3D-IDE:

cd 3D-IDE

# 1. main data
unzip 3d_ide_data.zip -d data/

# 2. scannet raw data
unzip scannet_posed_images_part1.zip -d data/scannet/
unzip scannet_posed_images_part2.zip -d data/scannet/
unzip scannet_mask_pcd.zip          -d data/scannet/

# 3. VGGT features (note: archives contain scene dirs directly, no wrapper)
mkdir -p data/scannet/posed_images_3d_feature_vggt
for i in 1 2 3 4 5 6 7 8 9; do
    unzip vggt_features_part$i.zip -d data/scannet/posed_images_3d_feature_vggt/
done

Verify (instead of re-downloading)

If you already prepared data and want to check it matches ours exactly:

cd 3D-IDE/data
md5sum -c md5_manifest.txt           # json / metadata / embodiedscan
md5sum -c md5_manifest_scannet.txt   # posed_images / mask / pcd

Any FAILED line points at a file that differs from our training copy.

Not included (download separately)

Item	Where
`data/models/LLaVA-Video-7B-Qwen2/`	lmms-lab/LLaVA-Video-7B-Qwen2
`VGGT_checkpoints/model.pt`	facebook/VGGT-1B

Final layout

3D-IDE/
├── data/
│   ├── balanced/
│   ├── benchmark/
│   ├── embodiedscan/
│   ├── metadata/
│   ├── models/LLaVA-Video-7B-Qwen2/      # separate download
│   ├── processed/
│   ├── multi.yaml
│   └── scannet/
│       ├── mask/
│       ├── pcd_with_object_aabbs/
│       ├── posed_images/
│       └── posed_images_3d_feature_vggt/
└── VGGT_checkpoints/model.pt             # separate download

Downloads last month: 16

Total file size:

477 GB

3D-IDE Training Data

Contents

Extraction

Verify (instead of re-downloading)

Not included (download separately)

Final layout