A Large-Scale Comprehensive Perception Dataset with High-Density Long-Range Point Clouds


News

May 25, 2021
Trajectory forecasting evaluation server is open. Everyone is welcome for benchmarking!
April 6, 2021
Data released and open to download here.

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About

  • Full sensor suite (3x LiDAR, 1x SPAD-LiDAR, 4x Radar, 5x RGB, 5x depth camera, IMU, GPS)
  • High-density and long-range LiDAR point cloud
  • Multi-echo point cloud from SPAD-LiDAR
  • 100 sequences with 1000 frames (100s) each
  • Out of distribution data including car crash and violation of traffic trules
  • 500,000 annotated images for 5 camera viewpoints
  • 100,000 annotated frames for each LiDAR/Radar sensor
  • 26M 2D/3D bounding boxes precisely annotated for 4 object classes (car, cyclist, motorcycle, pedestrian)
  • Object identity annotated across time to form trajectories
  • Object attributes such as percentage of truncation/occlusion, angular and linear velocity, acceleration, brake, steer, throttle
  • Sequential point cloud panoptic segmentation: All points annotated for 23 semantic classes in all sequences; Points belong to foreground objects are also annotated for a unique instance class.
  • Video panoptic segmentation: All pixels annotated for 23 semantic classes in all videos. Pixels belong to foreground objects are also annotated for a unique instance class.
  • Free to use for both non-commercial and commercial uses

Features

All-Inclusiveness

  • All sensors with 360° coverage, including RGB, stereo, depth, LiDAR, SPAD-LiDAR, Radar, IMU, GPS
  • Annotation for 2D/3D detection, tracking, forecasting, panoptic segmentation
  • Variations of adverse weather/lighting, crowded scenes, people running, high-speed driving, violations of traffic rule, car accidents (vehicle to vehicle/pedestrian/cyclist)

High-Density and Long-Range LiDAR

  • LiDAR data is at a range of 1K meters, ~8x beyond the range of Velodyne-64
  • LiDAR data has up to 1M points per frame, ~10x beyond the density of Velodyne-64
  • Our experiments show that high-density and long-range LiDAR enables more robust and early detection on small objects at a large distance, which is essential for planning, especially in high-speed driving

SPAD-LiDAR with Multiple Echos

  • Measure every single photon and generate a 3D tensor of photon counts of the scene
  • Provide point cloud with multiple returns (echoes) if the laser is partially reflected by multiple objects
  • Provide multi-echo reflectance, each measuring intensity of a single laser pulse return (echo)
  • Provide ambient image to simulate sunlight reflected by objects

Out-of-Distribution Data (Car Crash)

  • Vehicle driving off the road
  • Car went flying due to crash
  • Ego-vehicle tilted after being hit
  • Vehicle-to-pedestrian crash
  • Rear-end collision
  • Car flipped over after crash
  • Vehicle-to-cyclist crash
  • Multi-vehicle collision