Just some context here: * The raw data in nuscenes ( https://www.nuscenes.org/ https://www.nuscenes.org/ ) is about 5x larger than this dataset from Lyft. 300

Just some context here: * The raw data in nuscenes ( https://www.nuscenes.org/ https://www.nuscenes.org/ ) is about 5x larger than this dataset from Lyft. 300GB train vs 60GB train. Argoverse ( https://www.argoverse.org/ https://www.argoverse.org/ ) is is about 3.x larger at 200GB. The Waymo dataset will (allegedly) be an order of magnitude larger than nuscenes ( https://i2.wp.com/syncedreview.com/wp-content/uploads/2019/06/image-55.png?resize=1024%2C768&ssl=1 https://i2.wp.com/syncedreview.com/wp-content/uploads/2019/0... ). BDD100k ( https://bair.berkeley.edu/blog/2018/05/30/bdd/ https://bair.berkeley.edu/blog/2018/05/30/bdd/ ) is the "largest" public dataset to date, but lacks lidar, and labels are inconsistent; most of the 100,000 scenes only have one labeled frame. * The Lyft sensor suite has bumper-mounted lidar, which is absent from other existing datasets. Point cloud data in these areas is critical for pedestrians, bikes, and various road hazards. So this dataset alone is useful for validating work trained through other means. * The current Lyft Level 5 release has no explicit test / validation set, which is crucial for properly measuring performance of any experiment one might do with the data. In nuscenes and Argoverse, there's a small snippet dataset that helps you prepare your pipeline. Feels like Lyft might have rushed things a little here-- they could have posted a "teaser" and then the full train and test/validation set a couple weeks later. Great to see more public data (especially from a more modern sensor suite), plus investment into a contest with prizes.