Human "dynamic range" is a hack - the limits look impressive, but they're only reachable through a lengthy adaptation process. Modern camera sensors with HDR, backside illumination and analog gain controls get pretty close to that - and much, much faster.

In practice, if you want really good performance across an extreme dynamic range, it's usually easier to stack multiple specialized sensors within a single sensor unit. A filter-free reduced resolution sensor for high QE in low light conditions (or at high framerates), and a daylight-optimized sensor that gets high resolution, full Bayer, IR-cut and a polarized glare filter to get you as much data as it can in high light environments. This gives you straight up superhuman range with no adaptation time.

Do the raw low light images look nice? No. But human brain itself takes a lot of postprocessing for "looks nice" to happen. Salvaging good images from series of noisy measurements is an AI problem. We've had some pretty capable sensors for a while now, but it took AI-powered computational photography to truly make low light photography happen on a smartphone.

I'm aware of the "detection of individual photons at above-chance rates" experiments with human vision. But modern backside illuminated CMOS, if plugged into the same setup, would also be able to detect photons at above-chance rates. Not to mention the actual photon event cameras. Very niche items, but they can detect photons pretty reliably - not merely "more likely to be right than wrong".

There are also thermal imagers and image intensifier stages, if you want to take the "niche extreme sensors" route. Not commonly done. But goes to show just how much ass engineered sensors can kick.

The limits aren't in the sensors - it's in making sense of the data they give you.