A method of detecting and tracking a vehicle near a host vehicle, the method comprising: receiving, by an electronic controller, an input image from a camera mounted on the host vehicle; applying, by the electronic controller, a neural network configured to provide an output defining a plurality of three-dimensional bounding boxes, each three-dimensional bounding box indicating a size and a position of a different one of a plurality of vehicles detected in a field of view of the input image, wherein each three-dimensional bounding box is defined by the output of the neural network as a set of structured points defining a first quadrilateral shape outlining a rear or front of the detected vehicle and a second quadrilateral shape outlining a side of the detected vehicle, wherein the first quadrilateral shape is adjacent to the second quadrilateral shape; displaying an output image on a display screen, the output image including at least a portion of the input image and an indication of the three-dimensional bounding boxes overlaid onto the input image; characterized by: receiving a first user input indicative of a selection of a location on the output image outside of the three-dimensional bounding boxes; determining, based on the first user input, that an undetected vehicle is present within the field of the input image at the location corresponding to the user input; prompting a user to manually position a further three-dimensional bounding box relative to the undetected vehicle in the input image; defining a further three-dimensional bounding box based on a second user input received in response to the prompt; and retraining the neural network based on the user input indicative of the undetected vehicle, wherein retraining the neural network includes retraining the neural network to output the further three-dimensional bounding box based at least in part on the input image. receiving, by an electronic controller, an input image from a camera mounted on the host vehicle; applying, by the electronic controller, a neural network configured to provide an output defining a plurality of three-dimensional bounding boxes, each three-dimensional bounding box indicating a size and a position of a different one of a plurality of vehicles detected in a field of view of the input image, wherein each three-dimensional bounding box is defined by the output of the neural network as a set of structured points defining a first quadrilateral shape outlining a rear or front of the detected vehicle and a second quadrilateral shape outlining a side of the detected vehicle, wherein the first quadrilateral shape is adjacent to the second quadrilateral shape; displaying an output image on a display screen, the output image including at least a portion of the input image and an indication of the three-dimensional bounding boxes overlaid onto the input image; characterized by: receiving a first user input indicative of a selection of a location on the output image outside of the three-dimensional bounding boxes; determining, based on the first user input, that an undetected vehicle is present within the field of the input image at the location corresponding to the user input; prompting a user to manually position a further three-dimensional bounding box relative to the undetected vehicle in the input image; defining a further three-dimensional bounding box based on a second user input received in response to the prompt; and retraining the neural network based on the user input indicative of the undetected vehicle, wherein retraining the neural network includes retraining the neural network to output the further three-dimensional bounding box based at least in part on the input image. receiving a first user input indicative of a selection of a location on the output image outside of the three-dimensional bounding boxes; determining, based on the first user input, that an undetected vehicle is present within the field of the input image at the location corresponding to the user input; prompting a user to manually position a further three-dimensional bounding box relative to the undetected vehicle in the input image; defining a further three-dimensional bounding box based on a second user input received in response to the prompt; and retraining the neural network based on the user input indicative of the undetected vehicle, wherein retraining the neural network includes retraining the neural network to output the further three-dimensional bounding box based at least in part on the input image.