[dognotdog]

I'm not so convinced I'm seeing the limits of resolution, either angular or depth.

Using parallax to calculate depth undoubtedly has principal limitations in far away details, and mapping to an 8-bit depth buffer is another very reductive step in that regard. (regardless, I'd expect even the folds to show up, at least qualitatively, if I'd looked at an 8-bit rendering of a 3D scene's z-buffer; the gradient contour steps are clearly visible, and dense, yet fail to follow the folds, indicating that the underlying depth data simply doesn't track them at all)

Let's take the sleeves then -- clearly a large difference in relative depth, yet they blend into the rest of the garment. My impression is very much that of standard depth reconstruction "AI" that more or less guesses depths of a few image features, and does some DNN magic around where to blend smoothly and where to allow discontinuities, with the usual "weirdness" around features that don't quite fit the training sets.

Possibly all we can get out of this "parallax" method of depth reconstruction isn't a whole lot better than just single image deep learning, which would not surprise me, as it ultimately relies on the same approach for correctly recognizing and mapping image features across the 9 constituent images in the first place, vs. a true lightfield sensor that captures the actual direction of incoming light.