mlsanityData to 7 Oct 2026

Bosch Street Dataset: A Multi-Modal Dataset with Imaging Radar for Automated Driving

arXiv 2407.12803 ↗First posted 24 Jun 2024cs.CV cs.AIcited by 7

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Abstract (arXiv)

This paper introduces the Bosch street dataset (BSD), a novel multi-modal large-scale dataset aimed at promoting highly automated driving (HAD) and advanced driver-assistance systems (ADAS) research. Unlike existing datasets, BSD offers a unique integration of high-resolution imaging radar, lidar, and camera sensors, providing unprecedented 360-degree coverage to bridge the current gap in high-resolution radar data availability. Spanning urban, rural, and highway environments, BSD enables detailed exploration into radar-based object detection and sensor fusion techniques. The dataset is aimed at facilitating academic and research collaborations between Bosch and current and future partners. This aims to foster joint efforts in developing cutting-edge HAD and ADAS technologies. The paper describes the dataset's key attributes, including its scalability, radar resolution, and labeling methodology. Key offerings also include initial benchmarks for sensor modalities and a development kit tailored for extensive data analysis and performance evaluation, underscoring our commitment to contributing valuable resources to the HAD and ADAS research community.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 20 of its 31 references that are in the map. First posted on arXiv 24 Jun 2024.

Builds on

20 of 31 references.

References · 20

  1. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,485
  2. 2019Scalability in Perception for Autonomous Driving: Waymo Open Datasetcited by 2,436
  3. 2020Center-based 3D Object Detection and Trackingcited by 1,143
  4. 2023Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecastingcited by 701
  5. 2021One Million Scenes for Autonomous Driving: ONCE Datasetcited by 218
  6. 2019The Oxford Radar RobotCar Dataset: A Radar Extension to the Oxford RobotCar Datasetcited by 133
  7. 2022K-Radar: 4D Radar Object Detection for Autonomous Driving in Various Weather Conditionscited by 107
  8. 2020RADIATE: A Radar Dataset for Automotive Perception in Bad Weathercited by 98
  9. 2023Zenseact Open Dataset: A large-scale and diverse multimodal dataset for autonomous drivingcited by 83
  10. 2022TJ4DRadSet: A 4D Radar Dataset for Autonomous Drivingcited by 74
  11. 2023Far3D: Expanding the Horizon for Surround-view 3D Object Detectioncited by 70
  12. 2021Raw High-Definition Radar for Multi-Task Learningcited by 69
8 more
  1. 2021RadarScenes: A Real-World Radar Point Cloud Data Set for Automotive Applicationscited by 61
  2. 2022Improved Orientation Estimation and Detection with Hybrid Object Detection Networks for Automotive Radarcited by 33
  3. 2023Dual Radar: A Multi-modal Dataset with Dual 4D Radar for Autonomous Drivingcited by 32
  4. 2022aiMotive Dataset: A Multimodal Dataset for Robust Autonomous Driving with Long-Range Perceptioncited by 29
  5. 2022Pointillism: Accurate 3D bounding box estimation with multi-radarscited by 22
  6. 2021PixSet : An Opportunity for 3D Computer Vision to Go Beyond Point Clouds With a Full-Waveform LiDAR Datasetcited by 20
  7. 2024The Radar Ghost Dataset -- An Evaluation of Ghost Objects in Automotive Radar Datacited by 4
  8. 2023Exploiting Sparsity in Automotive Radar Object Detection Networkscited by 2

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Cited by year

Citing papers per year: 2024: 1; 2025: 6.

7 papers.