YAML Metadata Warning: The task_categories "autonomous-driving" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

YAML Metadata Warning: The task_categories "road-scene-understanding" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

CARD – Germany Batch 3 (Munich-> Ingolstadt)

A comprehensive multi-modal driving dataset with stereo cameras, LiDAR, and depth annotations.

Dataset Structure

This dataset contains 30 sequences across 1 region(s):

germany_batch3: 30 sequences

Data Format

Each sequence contains:

img/: Stereo camera images (cam_0, cam_1)
raw/: Raw sensor data
labels/: YOLO-format annotations
export/: Trajectory and calibration data
agg_depth/: Aggregated depth point clouds

License and Usage Terms

When using this dataset, you must give appropriate credit, provide a link to the license, and indicate if changes were made. You may use the data for commercial and non-commercial purposes.

For the full legal text, please see the official CC BY 4.0 page:

Human-readable summary: https://creativecommons.org/licenses/by/4.0/
Legal code: https://creativecommons.org/licenses/by/4.0/legalcode

We have taken reasonable measures to remove personally identifiable information (e.g., faces and license plates). To request removal of specific images from the dataset, please contact privacy@card-dataset.org.

The purpose of the CARD project is to help improve road safety. We encourage use of this dataset toward that goal; it is not intended for military use.

Note: CC BY 4.0 permits commercial use and adaptation without a share-alike requirement, as long as appropriate attribution is provided.

Development Kit

A development kit (CARD-SDK) with tools to get started is released separately and licensed under the MIT License.

Citation

@dataset{card_germany_2days,
  title   = {{CARD} – Germany 2 Days},
  author  = {{CARD-Data}},
  year    = {2025}
}

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