>high-fidelity data from 13 high-resolution cameras
is it me or their example photo doesn't look even like 1 high-resolution camera (and very noisy at that, looks like a pretty high ISO setting). Their example looks similar and i'd say a bit worse than what my Fuji camera did 25 years ago in the dark after i'd adjust dynamic range of the image in GIMP. (and the cameras on the Waymo cars i see around have about the same lens size as my Fuji)
If it is really a showcase of their visual pipeline than it makes sense that they are still so reliant on lidar - which is pretty expensive because of the number of rays you have to support to maintain good situation-awareness and which is still hard and expensive to scale to get good resolution. That also means that their tech can't really be put onto other platforms like drones for example.
Absolutely not an expert on this, but I would imagine that they would train the pipeline on a raw-ish image data to have better consistency? I would think that some kind of algorithm "bettering" the image suddenly might cause a discontinuation in the pipeline that is harder to account for versus the ML machinery being trained to do this job as well.
Also, what looks good to us may not be "good" to a machine.
But I'm really just guessing in the dark here.