I work in the AV space. There's a lot of ambiguity in labeling. How should a crowd of people be annotated? A line of parked cars? A photograph of a car? Examine the training set!
A big thing is not that the example is missing, but that it counts as a negative example. I.e. if during training a ML system notices the ambiguous combination (i.e. a woman pushing a baby stroller or a crowd) and marks it as a pedestrian, then it gets penalized in a manner that teaches it to ignore these ambigious combinations and treat it as nothing; while in practice it should probably treat such ambiguous combina…
Sooner or later it'd be nice to be able to drive one of these things in a place that isn't southern California.