Dataset Viewer
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
0001: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0002: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0003: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0004: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0005: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0006: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0007: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0008: struct<v1: string, v2: string,
...
ild 4, d: string
child 5, a: string
0618: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0619: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0620: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0621: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0622: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0623: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0624: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
to
{'0001': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0002': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0003': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0004': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0005': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0006': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0007': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0008': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0009': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0010': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0011': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0012': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Valu
...
': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0302': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0303': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0304': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0305': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0306': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0307': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0308': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0309': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0310': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0311': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0312': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}}
because column names don't match
Traceback: 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 295, 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 128, 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 2321, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
0001: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0002: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0003: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0004: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0005: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0006: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0007: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0008: struct<v1: string, v2: string,
...
ild 4, d: string
child 5, a: string
0618: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0619: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0620: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0621: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0622: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0623: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
0624: struct<v1: string, v2: string, q: string, c: string, d: string, a: string>
child 0, v1: string
child 1, v2: string
child 2, q: string
child 3, c: string
child 4, d: string
child 5, a: string
to
{'0001': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0002': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0003': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0004': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0005': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0006': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0007': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0008': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0009': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0010': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0011': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0012': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Valu
...
': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0302': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0303': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0304': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0305': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0306': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0307': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0308': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0309': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0310': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0311': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}, '0312': {'v1': Value('string'), 'v2': Value('string'), 'q': Value('string'), 'c': List(Value('string')), 'a': Value('string')}}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
MotionHalluc Benchmark
This repository contains the MotionHalluc benchmark, a dataset designed for evaluating motion hallucination and motion reasoning in video-based multimodal models.
📌 Overview
MotionHalluc introduces three evaluation tasks that require models to compare, reason about, and verify human motion patterns across videos. The benchmark is constructed using curated annotations and motion representations derived from human motion estimation pipelines.
We provide:
- Structured QA annotations for motion reasoning
- Motion representations extracted using a state-of-the-art motion reconstruction model
- Evaluation-ready dataset splits
📁 Dataset Structure
1. anno/
Contains all annotation files, including:
- Three MotionHalluc tasks (QA-based evaluation)
- Original curated annotations used to construct the benchmark
Each file is in JSON format.
2. motion_4dHumans/
Contains motion representations corresponding to each video sample.
- Format:
.npy - Extracted using a pretrained 4D human motion reconstruction pipeline
- Each file corresponds to a video ID used in the QA annotations
🎥 Video Data
We distribute annotations and motion representations only.
Since we do not own the original videos, users are required to download them separately.
- Fit3D dataset: https://fit3d.imar.ro/
The videos are used solely as input references for motion extraction and evaluation alignment.
⚙️ Motion Extraction
Motion representations are obtained using a pretrained 4D human motion reconstruction method:
@inproceedings{goel2023humans,
title={Humans in 4d: Reconstructing and tracking humans with transformers},
author={Goel, Shubham and Pavlakos, Georgios and Rajasegaran, Jathushan and Kanazawa, Angjoo and Malik, Jitendra},
booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
pages={14783--14794},
year={2023}
}
This approach is used to extract 3D human motion trajectories from video inputs.
💻 Preprocessing & Evaluation Code
We provide video processing and evaluation scripts in the official code repository:
👉 GitHub repository: https://anonymous.4open.science/r/MotionHalluc-4E96
This includes:
- Video preprocessing pipeline.
- Evaluation scripts for all three MotionHalluc tasks.
- Accuracy calculation script.
🔄 Fit3D Ground Truth Motion Processing
Due to dataset licensing restrictions, we do not redistribute Fit3D-derived motion data.
However:
- We will release the full Fit3D ground-truth motion processing pipeline upon acceptance.
- This includes conversion from raw motion capture format to our benchmark representation.
In the current submission, all experiments are conducted using the 4D-Humans-based motion representation, which already demonstrates strong performance and serves as a reliable proxy for kinematic evaluation.
📊 Benchmark Usage
Each sample in MotionHalluc contains:
- A question about motion comparison or reasoning
- Multiple-choice or binary answers
- Corresponding motion representation for each video
Example format:
{
"0001": {
"v1": "Bench/s03/band_pull_apart/band_pull_apart_front_215_304.mp4",
"v2": "Bench/s04/band_pull_apart/band_pull_apart_front_236_345.mp4",
"q": "You are given a query motion in Video1 and a reference motion in Video2. Which of the following correction accurate and necessary to improve the query motion in Video1 based on the reference motion in Video2?",
"c": [
"Hands level with your head at the beginning",
"At the beginning, keep your hands below head level"
],
"a": "A"
},
}
📜 License
This dataset is released for non-commercial scientific research purposes only.
- The annotation data and benchmark design are released under the CC BY 4.0 License.
- Motion representations are derived from a pretrained human motion reconstruction model.
- Video data is not redistributed due to licensing restrictions and must be obtained from the original source.
Users must comply with the license terms of all underlying datasets used in this benchmark, including the Fit3D dataset.
📌 Citation
Citation for Fit3d and 4D-Human:
@inproceedings{fieraru2021aifit,
title={Aifit: Automatic 3d human-interpretable feedback models for fitness training},
author={Fieraru, Mihai and Zanfir, Mihai and Pirlea, Silviu Cristian and Olaru, Vlad and Sminchisescu, Cristian},
booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
pages={9919--9928},
year={2021}
}
@inproceedings{goel2023humans,
title={Humans in 4d: Reconstructing and tracking humans with transformers},
author={Goel, Shubham and Pavlakos, Georgios and Rajasegaran, Jathushan and Kanazawa, Angjoo and Malik, Jitendra},
booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
pages={14783--14794},
year={2023}
}
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