What are the techniques (and the papers thereof) that you consider to be spectacularly good before 2021 for depth estimation, monocular or not?

I do some tangent work from this field for applications in robotics, and I would consider (metric) depth estimation (and 3D reconstruction) starting to be solved only by 2025 thanks to a few select labs.

Car vision has some domain specificity (high similarity images from adjacent timestamps, relatively simpler priors, etc) that helps, indeed.

A mech eng PhD said that he watches Gundam/Macross for drama and Romance (as in Romanticism).

The challenges you mentioned, and techniques to address them, are not unique to quantum physics. I am still not understanding how quantum physics require "new" kind of numerical analysis. And what are these new kinds of techniques you hint at? Could you give me some examples of unique techniques that arose from quantum physics and are not used elsewhere?

PDEs are PDEs, regardless of where they come from Newtonian or quantum. Would you care to elaborate why you think quantum requires a new kind of numerical analysis?