Understanding Dynamic Scenes in Ego Centric 4D Point Clouds
Paper
•
2508.07251
•
Published
•
1
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: UnidentifiedImageError
Message: cannot identify image file <_io.BytesIO object at 0x7f6ba50ee390>
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 2543, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2061, in __iter__
batch = formatter.format_batch(pa_table)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/formatting/formatting.py", line 472, in format_batch
batch = self.python_features_decoder.decode_batch(batch)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/formatting/formatting.py", line 234, in decode_batch
return self.features.decode_batch(batch, token_per_repo_id=self.token_per_repo_id) if self.features else batch
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2161, in decode_batch
decode_nested_example(self[column_name], value, token_per_repo_id=token_per_repo_id)
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1419, in decode_nested_example
return schema.decode_example(obj, token_per_repo_id=token_per_repo_id) if obj is not None else None
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/image.py", line 190, in decode_example
image = PIL.Image.open(bytes_)
^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/PIL/Image.py", line 3498, in open
raise UnidentifiedImageError(msg)
PIL.UnidentifiedImageError: cannot identify image file <_io.BytesIO object at 0x7f6ba50ee390>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.
EgoDynamic4D Dataset from AAAI 2026 paper: Understanding Dynamic Scenes in Egocentric 4D Point Clouds
🚀 EgoDynamic4D QA dataset has been released.
This repository hosts the official implementation of EgoDynamic4D, a large-scale egocentric 4D dynamic scene understanding benchmark introduced in our AAAI 2026 paper:
Understanding Dynamic Scenes in Egocentric 4D Point Clouds
About the Dataset
EgoDynamic4D is a question answering (QA) benchmark designed for fine-grained spatio-temporal reasoning in egocentric dynamic scenes.
The dataset includes:
- Egocentric RGB-D videos
- Camera poses
- Globally unique instance masks
- 4D bounding boxes over time
- Large-scale QA annotations for dynamic reasoning tasks
The dataset is constructed based on existing egocentric 4D resources, building upon ADT and THUD++. Our main contribution lies in the large-scale, task-driven QA annotations, which enable fine-grained spatio-temporal reasoning in dynamic egocentric scenes.
Please find instructions on Github for usages.
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