2D Detection: Given a set of camera images, produce a set of 2D boxes for the objects in the scene.

Given a set of camera images, produce a set of 2D boxes for the objects in the scene. 2D Tracking: Given a temporal sequence of camera images, produce a set of 2D boxes and the correspondences between boxes across frames.

Given a temporal sequence of camera images, produce a set of 2D boxes and the correspondences between boxes across frames. 3D Detection: Given one or more lidar range images and the associated camera images, produce a set of 3D upright boxes for the objects in the scene.

Given one or more lidar range images and the associated camera images, produce a set of 3D upright boxes for the objects in the scene. 3D Tracking: Given a temporal sequence of lidar and camera data, produce a set of 3D upright boxes and the correspondences between boxes across frames.

Given a temporal sequence of lidar and camera data, produce a set of 3D upright boxes and the correspondences between boxes across frames. Domain Adaptation: Similar to the 3D Detection challenge, but we provide additional segments from rainy Kirkland, Washington, 100 of which have 3D box labels.

1st place: $15,000

$15,000 2nd place: $5,000

$5,000 3rd place: $2,000

Waymo’s Open Dataset Challenges start today and will run until May 31, 2020, while the leaderboard will remain open for future submissions. Challenge winners will be given the opportunity to present their work at our Workshop on Scalability in Autonomous Driving at CVPR 2020 in Seattle on June 14, 2020, or depending on developments, other suitable venues.Good luck and stay healthy and safe.