Color me extremely skeptical. A low-pass filter will make short work of any "tiny, pixel-level" changes designed to thwart ML. After all, one of the most tell-tale identifiers (space between eyes/nose/mouth) is still plainly observable and unaltered in the "cloaked" image. If a human's neural network can correctly correlate the before/after examples, so can a computer's. They might have found an issue with some moder…
From the linked article: Q: Can't you just apply some filter, or compression, or blurring algorithm, or add some noise to the image to destroy image cloaks? A: As counterintuitive as this may be, the high level answer is no simple tools work to destroy the perturbation that form image cloaks. To make sense of this, it helps to first understand that Fawkes does not use high-intensity pixels, or rely on bright patterns…
First, a source image at an approximate resolution that you might find on a social networking site: https://imgur.com/a/9szcC1m
Text output of the tool, which ran for about 3 minutes: https://imgur.com/a/fZtfrmm
The resulting cloaked image: https://imgur.com/a/OSHXdbO
I applied a difference filter between the two images in Photoshop, to show an example of the actual pertubations performed: https://imgur.com/a/q4zC7Ms
Since it's hard to see, I compressed the output to highlight what the program actually changed. It does seem like there is a good amount of disturbance to the image: https://imgur.com/a/1Sx68o3
Now, the real test. First, a Google reverse image search for the original file - identification is pretty bang-on: https://imgur.com/a/5HJwjPx
A Google reverse image search for the cloaked file: https://imgur.com/a/QByXBfS
The only difference I'm seeing is a few images that are one or two images swapped in the "visually similar images" category.
So, I figured that that's the "best case" for the cloaked image - giving the search algorithm the full, unfiltered data, and the program still failed to disguise it. For fun, I thought I would use a "low-pass filter" (Google Lens pointed at my computer screen) as well, just for thoroughness. And the result surprised me!
Here's Google Lens pointed at my screen with the original image open: https://imgur.com/a/1BVRFG0
And here's Google Lens pointed at my screen with the cloaked image open: https://imgur.com/a/uoppuit
So, it would seem that the algorithm's distortions more effectively come through in worse quality images! But, based on my full-resolution result, I wouldn't trust it to disguise something that is being directly uploaded to a social network.
Now, one important note is that reverse image search is probably not using a facial recognition model, but more like image chunk hashing - although I would also consider that something a privacy tool should defend against, which is why I included it.
All in all, very interesting and thanks for convincing me that I should actually test it out.