Sensor Virtualization

Abstract

The present invention relates to a method for training a neural network to predict objects in the vicinity of a vehicle, comprising the steps of: acquiring physical sensor data from a physical sensor having one or more modalities; performing a first mapping from the physical sensor data to the virtual sensor data to obtain the virtual sensor data; performing a second mapping from the virtual sensor data to the 3D model space; and training a neural network based on the virtual sensor data and one or more annotations in the 3D model space.

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