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PandaSet: Advanced Sensor Suite Dataset for Autonomous Driving (2112.12610v1)

Published 23 Dec 2021 in cs.CV and cs.RO

Abstract: The accelerating development of autonomous driving technology has placed greater demands on obtaining large amounts of high-quality data. Representative, labeled, real world data serves as the fuel for training deep learning networks, critical for improving self-driving perception algorithms. In this paper, we introduce PandaSet, the first dataset produced by a complete, high-precision autonomous vehicle sensor kit with a no-cost commercial license. The dataset was collected using one 360{\deg} mechanical spinning LiDAR, one forward-facing, long-range LiDAR, and 6 cameras. The dataset contains more than 100 scenes, each of which is 8 seconds long, and provides 28 types of labels for object classification and 37 types of labels for semantic segmentation. We provide baselines for LiDAR-only 3D object detection, LiDAR-camera fusion 3D object detection and LiDAR point cloud segmentation. For more details about PandaSet and the development kit, see https://scale.com/open-datasets/pandaset.

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Authors (12)
  1. Pengchuan Xiao (2 papers)
  2. Zhenlei Shao (2 papers)
  3. Steven Hao (3 papers)
  4. Zishuo Zhang (1 paper)
  5. Xiaolin Chai (1 paper)
  6. Judy Jiao (1 paper)
  7. Zesong Li (2 papers)
  8. Jian Wu (314 papers)
  9. Kai Sun (317 papers)
  10. Kun Jiang (128 papers)
  11. Yunlong Wang (91 papers)
  12. Diange Yang (37 papers)
Citations (155)

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