END-TO-END TRAINABLE ADVANCED DRIVER-ASSISTANCE SYSTEMS

The disclosed systems and techniques are directed to computationally efficient detection and tracking of objects in driving environments. The techniques include generating a set of auto-labeled training data using a first autonomous vehicle (AV) system having multiple sensor modalities. The auto-labeled training data includes a first set of non-lidar data associated with the first AV system, and one or more target predictions for the first set of non-lidar data, said predictions generated based at least on lidar data associated with the first AV system. The techniques further include training, by the processing device and using the auto-labeled training data, an end-to-end perception model of a second AV system lacking a lidar sensor to predict presence of one or more objects in a driving environment of the second AV system.