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Terms and conditions:
The KITScenes dataset is provided to you under a Creative Commons Attribution-NonCommercial 4.0 International Public License (CC BY-NC 4.0), with the additional terms included herein. When you download or use the dataset, you are agreeing to comply with the terms of CC BY-NC 4.0 as applicable, and also agreeing to the dataset terms (listed below). Where these dataset terms conflict with the terms of CC BY-NC 4.0, these dataset terms shall prevail.
Dataset terms:
- In case you use the dataset within your research papers, you refer to our respective publication. If the dataset is used in media, a link to our websites (kitscenes.com) is included.
- We take steps to protect the privacy of individuals by anonymizing faces and license plates using state-of-the-art anonymization software from BrighterAI. To the extent that you like to request removal of specific images/data frames from the dataset, please contact info@mrt.kit.edu.
- We reserve all rights that are not explicitly granted to you. The dataset is provided as is, and you take full responsibility for any risk of using it.
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KITScenes Multimodal Dataset Sample
Preview sample. This repository provides a small preview of the KITScenes Multimodal dataset and contains a single sequence for browsing and inspection.
This sample repository is a lightweight preview of the KITScenes Multimodal dataset. It is intended to let users inspect the data format and browse a representative sequence.
What is included
This sample release contains one representative sequence for exploration.
Sequence structure
Each sequence is organized by modality and derived data products. In this sample, the top-level layout includes:
- camera folders: one high-resolution front camera, stereo cameras, and six ring cameras for 360° coverage
- lidar folders: seven lidars covering front, rear, left, right, both corners, and the roof-mounted top lidar
- radar folders: front, left, and right radar scams
- gnss / gnss_ins: pose, velocity, navigation, and status messages in synchronized per-topic folders
- async: asynchronous GNSS and GNSS/INS message streams
- calibration: sensor calibration in a JSON file
- maps: map data for the sample area
- processed: derived outputs such as ground segmentation and selected image instance predictions
Concretely, the camera data is split into folders such as camera_base_front_center, camera_base_front_left_rect, camera_base_front_right_rect, and the six camera_ring_* views. The processed subfolder contains examples of downstream artifacts, including per-lidar ground segmentation and seamseg_instances for selected ring cameras.
About KITScenes Multimodal
KITScenes Multimodal is a high-fidelity autonomous driving dataset designed for research toward production-grade urban driving. It focuses on complex European city environments and combines high resolution synchronized cameras, long-range lidar, 4D imaging radar, GNSS/INS localization, and production-grade Lanelet2 HD maps, the most complete HD maps of any sensor dataset to date.
Intended use of this sample
This repository is intended for:
- browsing and visual inspection of the data
- checking file structure and metadata conventions
- validating data loaders and preprocessing pipelines
- quick qualitative experiments on a single scene
This sample is not intended as a benchmark release and should not be used for quantitative performance claims about full-dataset generalization.
Full dataset access
The full KITScenes Multimodal dataset contains substantially broader geographic coverage, richer annotations, and official benchmark splits. If you need the complete dataset for research use, please refer to the main KITScenes Multimodal dataset repository:
Access and license
This sample is provided under CC BY-NC 4.0. Please refer to the main KITScenes dataset repository for the full access terms, usage conditions, and any additional dataset-specific requirements:
Citation
If you use KITScenes Multimodal in research, please cite the associated KITScenes Multimodal publication. A full citation entry and paper will be added together with the full release.
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