CVPR 2019 WAD Challenge on Trajectory Prediction and 3D Perception
It addresses benchmarking and community engagement for autonomous driving research, but is incremental as it focuses on a specific challenge and dataset.
This paper reviews a CVPR 2019 challenge on autonomous driving, which tackled trajectory prediction and 3D perception using a dataset of 150 minutes of labeled data, 80k lidar point clouds, and 1000km trajectories, with over 200 teams submitting results.
This paper reviews the CVPR 2019 challenge on Autonomous Driving. Baidu's Robotics and Autonomous Driving Lab (RAL) providing 150 minutes labeled Trajectory and 3D Perception dataset including about 80k lidar point cloud and 1000km trajectories for urban traffic. The challenge has two tasks in (1) Trajectory Prediction and (2) 3D Lidar Object Detection. There are more than 200 teams submitted results on Leaderboard and more than 1000 participants attended the workshop.