Hi.
I am developing on lane detection using CULane dataset.
I have a one question about lane detection.
In general, 5 classes(background + 4 lanes) are used for lane detection.
Some open source only use 4 lane classes without background class.
When learning, is there a big difference in performance between classifying the background and not doing it?