Other types of ML-camouflage, like https://cvdazzle.com/, make the wearer stand out far too much to actually be useful as anything but an art project.
I don't what became of the 'infra-red baseball cap' discussed in the article. In my opinion, it not only seems like a different approach, but also feels innocuous, compared to some of the other methods.
Various companies have been implementing appearance search functionality that lets you search for similar appearances across multiple cameras to find the scene/image where you got a facial shot of a person of interest. Preventing the majority of cameras from classifying someone as a "person" object would significantly disrupt that workflow.
You cannot stop the camera to be there or aiming at you, so realistically the best option is to rely on a timeless principle: modifying input information will lead to changes of its output result, since the second element will always depend on the first.
I can see this is going to be another cat and mouse game in the near future. People are going to constantly come up with new creative ideas to circumvent around machine learning since it can only accurately identify data which it has already seen.
Looks realistic, plausible and can be 3D printed (authors of the paper even provide the design sample).
None of these defeat old fashioned motion detection + followup by human eyes. Security guards arent going away anytime soon.
I can't see it being too difficult to identify tactics being used and mark them as suspicious.
I'm sure you're right. But remember what every security measure is trying to achieve -- it's not actually making you immune to attack (that's impossible), but rather to increase the cost of the attack.
This sort of thing would accomplish that by requiring human involvement.