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: Schema at index 1 was different:
lights: struct<0: struct<type: string, position: list<item: double>, intensity: double, color: list<item: double>>, 1: struct<type: string, position: list<item: double>, intensity: double, color: list<item: double>>, 2: struct<type: string, position: list<item: double>, intensity: double, color: list<item: double>>, 3: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 4: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 5: struct<type: string, position: list<item: double>, intensity: double, color: list<item: double>>, 6: struct<type: string, position: list<item: double>, intensity: double, color: list<item: double>>, 7: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 8: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 9: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 10: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 11: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 12: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 13: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 14: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 15: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>>
vs
lights: struct<0: struct<type: string, position: list<item: double>, intensity: double, color: list<item: double>>, 1: struct<type: string, position: list<item: double>, intensity: double, color: list<item: double>>, 2: struct<type: string, position: list<item: double>, intensity: double, color: list<item: double>>, 3: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 4: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 5: struct<type: string, position: list<item: double>, intensity: double, color: list<item: double>>, 6: struct<type: string, position: list<item: double>, intensity: double, color: list<item: double>>, 7: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 8: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 9: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 10: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 11: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 12: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 13: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 14: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>>
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 3496, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2257, in _head
return next(iter(self.iter(batch_size=n)))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2461, in iter
for key, example in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1952, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1974, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 531, in _iter_arrow
yield new_key, pa.Table.from_batches(chunks_buffer)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "pyarrow/table.pxi", line 5039, in pyarrow.lib.Table.from_batches
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: Schema at index 1 was different:
lights: struct<0: struct<type: string, position: list<item: double>, intensity: double, color: list<item: double>>, 1: struct<type: string, position: list<item: double>, intensity: double, color: list<item: double>>, 2: struct<type: string, position: list<item: double>, intensity: double, color: list<item: double>>, 3: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 4: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 5: struct<type: string, position: list<item: double>, intensity: double, color: list<item: double>>, 6: struct<type: string, position: list<item: double>, intensity: double, color: list<item: double>>, 7: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 8: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 9: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 10: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 11: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 12: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 13: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 14: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 15: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>>
vs
lights: struct<0: struct<type: string, position: list<item: double>, intensity: double, color: list<item: double>>, 1: struct<type: string, position: list<item: double>, intensity: double, color: list<item: double>>, 2: struct<type: string, position: list<item: double>, intensity: double, color: list<item: double>>, 3: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 4: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 5: struct<type: string, position: list<item: double>, intensity: double, color: list<item: double>>, 6: struct<type: string, position: list<item: double>, intensity: double, color: list<item: double>>, 7: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 8: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 9: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 10: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 11: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 12: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 13: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>, 14: struct<type: string, position: list<item: double>, intensity: double, color: list<item: int64>>>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.
Augmented ReplicaCAD Dataset
We present Augmented ReplicaCAD dataset. This dataset is part of OSMa-Bench pipeline.
What is Augmented ReplicaCAD?
The ReplicaCAD dataset is an artist recreation of the scanned “FRL apartment” variations from the Replica dataset. We augmented the original data with semantic masks to provide higher-quality ground-truth annotations for semantic segmentation tasks.
All materials are licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) Public License.
Dataset Contents:
ReplicaCAD offers two dataset variants: one designed for interactive simulation and another for photorealistic visualization with baked lighting. For our work, we selected the simulation-oriented version (without baked lighting) because it includes additional Habitat-specific metadata that enables loading and using semantic annotations.
Note: downloadable dataset contain 84 of the 105 variations described in the paper and shown in the video with the remaining 21 scenes (1 macro variation and associated 20 micro variations) withheld as a test set for challenge evaluation.
Follow the link for additional info: HuggingFace
Citing Augmented ReplicaCAD
Using Augmented ReplicaCAD in your research? Please cite following papers: OSMa-Bench arxiv and ReplicaCAD arxiv.
@inproceedings{popov2025osmabench,
title = {OSMa-Bench: Evaluating Open Semantic Mapping Under Varying Lighting Conditions},
author = {Popov, Maxim and Kurkova, Regina and Iumanov, Mikhail and Mahmoud, Jaafar and Kolyubin, Sergey},
booktitle = {2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
year = {2025}
}
@inproceedings{szot2021habitat,
title = {Habitat 2.0: Training Home Assistants to Rearrange their Habitat},
author = {Andrew Szot and Alex Clegg and Eric Undersander and Erik Wijmans and Yili Zhao and John Turner and Noah Maestre and Mustafa Mukadam and Devendra Chaplot and Oleksandr Maksymets and Aaron Gokaslan and Vladimir Vondrus and Sameer Dharur and Franziska Meier and Wojciech Galuba and Angel Chang and Zsolt Kira and Vladlen Koltun and Jitendra Malik and Manolis Savva and Dhruv Batra},
booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
year = {2021}
}
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