I've never understood this argument. Isn't the main bottleneck that you need well-labeled data for training the neural networks? How is having tons and tons of random camera footage going to help?
One way to think of this is that that the footage is implicitly labelled: we have the benefit of hindsight: we know what the state/location of the vehicle was going into the future. That benefit of hindsight also can serve as implicit labels by knowledge that the vehicle did not crash or collide with something immediately after the footage.