New Datasets to Accelerate Autonomous Driving Research

In the past month, several companies announced they will release new high-quality datasets for autonomous driving. One of these datasets is Waymo Open Dataset which was introduced at top AI conference Computer Vision and Pattern Recognition (CVPR) 2019 in Long Beach, California

In a talk at the CVPR 2019 Autonomous Driving Workshop, Waymo Principal Scientist said traditional open-source datasets like KITTI are too small and with little diversity for today’s leading autonomous driving companies, forcing researchers and engineers to spend too much time on data augmentation and on preventing overfitting. Moreover, algorithm results on KITTI could not generalize to large datasets.

All these reasons mentioned above, motivated Waymo to curate the Waymo Open Dataset, which features 3.000 driving scenes totalling 16.7 hours of video data, 600.000 frames, approximately 25 million 3D bounding boxes and 22 million 2D bounding boxes. Sensors on Waymo’s data-collection autonomous vehicles include five LiDARs, five cameras and an undisclosed number of radars. The company said that they were able to more accurately synchronize LiDAR and camera recordings than in open data (KITTI , NuScenes)

The Waymo Open Dataset also improves on data diversity, factoring in variables such as weather, pedestrians, lighting conditions, cyclists and construction.

Waymo will release the first part of the dataset with 1.000 videos in July, and more in the near future. The company will also publish benchmarks and organize competitions.

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