powertoold
Active Member
Interesting breakdown thread of a slide from AI Day by Whole Mars Blog:
Basically, they're using crowd-sourced data from multiple trips through an intersection. But they're not using it to create an HD map that would become stale relatively quickly; they're using it to generate ground-truth for training data labeling.
This approach has me questioning:
If they simply overlay the prior trip data to the current trip, who is there to make sure that the current trip is only labeled with what the car can see? I know they have a human label evaluator, but do they even care that occluded lanes / geometries are being labeled in the current trip? Wouldn't labeling things that the car can't see cause problems? I'm sure they've considered this, but it wasn't explained during AI Day.
No one here knows this, I'm just spitballing.