The auto labeling work (which has been partially described/presented at Tesla AI day events) seems more like engineering than research, a grab bag of techniques that I would guess the whole team must have contributed to. For example, they auto label low resolution/indeterminate objects (image segments) by temporal continuity... Something that is a low-res blob in the distance becomes a hi-res and easy to identify object when you drive by it, so by tracking objects backwards across frames you can learn how to more confidently label the lo-res blob. Things like this are useful, but it's the sort of stuff that engineers and developers are coming up with every day.

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ricardobeat an hour ago | parent [-]

Not back in 2016.

	▲	HarHarVeryFunny 41 minutes ago \| parent [-]
		You don't think that tracking objects from frame to frame is obvious ?! I can guarantee you this was built-in from day #1 I'm guessing you're not a developer if you don't then automatically think of end cases like "what if car # 1 isn't in the preceding frame" ... (then you look at some relevant test data and see it was there, unlabelled ...)