Data augmentation using computer simulated objects for autonomous control systems

A computer-implemented method of training an object detection model, comprising:

• obtaining a training dataset of images that represent a set of computer simulated vehicles with a known set of characteristics, the characteristics including geometric information of the computer simulated vehicles in the images;
• obtaining a training set of coordinates for the images that represent 3-D bounding boxes of the computer simulated vehicles, the 3-D bounding boxes enclosing an outer boundary of the computer simulated vehicles, and the training set of coordinates for the 3-D bounding boxes determined based on the geometric information of the computer simulated vehicles;
• and
• training a set of parameters of the object detection model using the training dataset of images, the training comprising repeatedly performing iterations of:
• generating a set of estimated coordinates by applying the object detection model with an estimated set of parameters to the training dataset of images,
• determining a loss function indicating a difference between the set of estimated coordinates and the training set of coordinates for the computer simulated vehicles, and
• updating the set of parameters of the object detection model to reduce the loss function.