The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 289, in get_dataset_config_info
for split_generator in builder._split_generators(
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 83, in _split_generators
raise ValueError(
ValueError: The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 65, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 343, in get_dataset_split_names
info = get_dataset_config_info(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 294, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.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.
A Multi-Vehicle Dataset with Camera, LiDAR, and Radar Sensors and Scanned 3D Models for Custom Auto-Annotation using RTK-GNSS
A dataset for autonomous driving, incorporating lidar, camera and radar sensors, seven simultaneous target vehicles with INS reference poses and 3D scans.
This repository hosts the dataset presented by a IEEE paper published to IEEE Sensor Data Fusion (SDF) 2025:
@InProceedings{7V-Scanario_2025,
author = {Philipp Berthold AND Bianca Forkel AND Mirko Maehlisch},
booktitle = {Symposium Sensor Data Fusion (SDF)},
title = {{A Multi-Vehicle Dataset with Camera, LiDAR, and Radar Sensors and Scanned 3D Models for Custom Auto-Annotation using RTK-GNSS}},
year = {2025}
}
Authors: Philipp Berthold*, Bianca Forkel*, and Mirko Maehlisch (* contributed equally)
Abstract: Datasets are a crucial element in the development of perception algorithms. They relate sensor measurement data to annotated reference information and allow for the deduction of sensor and object characteristics. In autonomous driving, the reference data commonly consist of semantic image segmentation, point-wise associations, or bounding box annotations. The dataset proposed in this work, however, aims to dig deeper into the evaluation of measurement principles and provides scanned 3D models of all vehicles together with a pose and continuous kinematics reference obtained by RTK-GNSS. Combined, the state of the complete dynamic surrounding of the sensor vehicle is known for any point in time. Subsequent reference formats can be easily computed in user-defined granularity. This dataset involves single-object and multi-object recordings with seven target vehicles. In particular, measurement effects such as occlusion, as well as reflections, can be evaluated, as the normals of the shape of the target vehicles are known. We describe the dataset, discuss the technical background of its development, and briefly present exemplary evaluations.
Dataset Details
Please find the documentation including example visualiation code for this dataset at: https://github.com/UniBwTAS/7V-Scanario
Intended Use
The dataset may be used for:
- Research and development in autonomous driving;
- Training, validation, and evaluation of machine learning models;
- Commercial research and development;
- Publication and distribution of trained machine learning models.
Prohibited Use
The following uses are explicitly prohibited:
- Identification or re-identification of natural persons appearing in the data;
- Biometric analysis or person recognition;
- Person-centric analysis or profiling;
- Extraction, annotation, or redistribution of subsets focusing on individuals;
- Combining the dataset with external data sources to infer personal identities;
- Distribution of derived datasets containing personal or potentially identifiable information.
Data Collection
Data was collected on a restricted area under controlled conditions. All participants were informed about the data collection and consented to the creation of a publicly released research dataset.
The dataset was not collected in public spaces, and no intentional recordings of identifiable individuals were performed.
Privacy and Ethical Considerations
While persons may be incidentally visible in the sensor data, they are not the focus of the dataset. Visibility of individuals is limited, and no personal annotations are provided.
Users of the dataset must ensure that their use complies with applicable privacy and data protection regulations and respects the rights of individuals.
License
This dataset is released under a Custom Dataset License.
- Research and commercial use is permitted;
- Training and publication of machine learning models is permitted;
- Redistribution of the dataset is allowed only with proper attribution;
- Re-identification and person-centric use is prohibited.
See the LICENSE file for full terms.
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