Massive Release of Open Data (Dataset)
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Scale and nuTonomy open-source massive AI dataset for self-driving cars
Scale Inc. and Aptiv PLC’s nuTonomy group, two influential players in the autonomous vehicle ecosystem, today open-sourced a massive research dataset designed to aid self-driving car initiatives.
Autonomous vehicles rely on artificial intelligence models to make navigation decisions. Those AI models, in turn, must be trained with large amounts of sample information to achieve the necessary accuracy, which is where the new dataset comes into the picture.
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Open Source Multi-Sensor Self-Driving Dataset Available To Public
Scale has released what it believes to be the largest open source multi-sensor (LIDAR, RADAR, and camera) self-driving dataset published by nuTonomy (acquired by Aptiv in 2017), with annotations by Scale. Academic researchers and autonomous vehicle innovators can access the open-sourced dataset, nuScenes.
The nuScenes open source dataset is based on LIDAR point cloud, camera sensor, and RADAR data sourced from nuTonomy and then labeled through Scale’s sophisticated and thorough processing to deliver data ideal for training autonomous vehicle perception algorithms. It provides the full dataset that includes 1,000 twenty-second scenes, nearly 1.4 million camera images, 400,000 LIDAR sweeps, and 1.1 million 3D boxes.
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