That is true up to a certain point (for instance, in my experience, having bounding boxes that are not pixel-perfect acts as a regularizer), but there is also a good chance that you are mislabelling edge cases, situations that happen rarely, and that definitely hurts the performance of the neural network to make a correct prediction on these difficult / uncommon scenarios.