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An image preprocessing tool to protect artworks from AI-for-Art based mimicry
- billconan 3y agothis only works for publicly released model weights, right? can it work for closed models, like midjourney?
- version_five 3y agoIt doesn't really work for anything. It would be trivial to defeat this.
- K0balt 3y agoWhile I share your reservations, I think we should either give it a whirl or wait for someone else to try adversarial processing before we dismiss it out of hand. My guess is though that if you had a training set of processed vs unprocessed pairs that you could train an “unmister” if you wanted to.
- TheRealPomax 3y agoNot much point in giving it a whirl when the resulting images are clearly not something you'd put in your site to show off your work. The problem with this (and glaze, etc) is that it does what it claims by ruining the image it's used on.
- spookie 3y agoUnfortunately it's the natural progression of the web, given the unethical ways people are training their models. This is going to happen in more ways than just images.
- K0balt 3y agoThe image degradation seems like certainly a potential dealbreaker from an art perspective. Perhaps in some modalities it would be less noticeable?
- bhickey 3y agoWe should dismiss it out of hand. Any image that a human can look at can be fed to a neural net. It's just an instance of the analog hole.
- roughly 3y ago> My guess is though that if you had a training set of processed vs unprocessed pairs that you could train an “unmister” if you wanted to. I look forward to the masterclass in ethical justification acrobatics that would accompany such an effort
- K0balt 3y agoClearly you haven’t met my in-laws.
- theaiquestion 3y agoFunny enough the first one I've found that works consistently with this one(however unusably destructive) is the "whirl" filter in GIMP. Previous adversarial methods I've beat with simple noise/blur. This one is fairly resistant to basic filters.
- canadianfella 3y ago[dead]
- openbear 3y agoI don’t see artists replacing all the images on their websites with Mist processed versions. Their example Van Gogh images look okay as thumbnails but are really different from the originals when viewed larger. Overall a neat project though.
- meepmorp 3y agoI think the thumbnails of the misted look awful, though that might be because I can see the original to compare. There seems to be weird semi-regular patterns around the images that I think I'd notice even without the comparison, though.
- soared 3y agoI could see use cases for galleries posting images of paintings/photos that are for sale in real life, but that they don’t want copies online.
- cratermoon 3y agoIt's definitely a work-in-progress.
- msp26 3y agoIf it's anything like Glaze, it's a complete meme. That took a lot of compute to glaze an image (with very visible artifacts) and was bypassed with some trival image processing on a shitty laptop.
- brucethemoose2 3y agoI don't think its meant to stop determined thieves, but rather automated web crawlers or more casual human copycats.
- polygamous_bat 3y agoWhy would automated web crawlers not throw the best de-Glazing techniques at their dataset before model training?
- greysphere 3y agoBecause it increases the cost.
- polygamous_bat 3y agoCompared to training a model on few thousand or more GPU-hours? Probably merit a footnote, at best.
- theaiquestion 3y agoJust for context LAOIN's largest dataset is 5.8 Billion images And you'd be spending that compute time for what will be a tiny, tiny,portion of that
- brucethemoose2 3y agoOn the off chance that a single digit percentage of the dataset is glazed, they would probably detect and exclude, as that is easier.
- LeftHandPath 3y agoThis is incredibly similar to a paper one of my professors was working on a year or two ago: [0] > Neural Trojans embedded in pre-trained neural networks are a harmful attack against the DNN model supply chain. They generate false outputs when certain stealthy triggers appear in the inputs. While data-poisoning attacks have been well studied in the literature, code-poisoning and model-poisoning backdoors only start to attract attention until recently. While I agree with other commenters here that it's hard to imagine it being widely implemented at the moment, I think it's only the beginning of this type of tech. In a few years, maybe this type of data poisoning could be as ubiquitous as SSL and as subtle as webp compression artifacting. [0]: https://dl.acm.org/doi/abs/10.1145/3548606.3560678 https://dl.acm.org/doi/abs/10.1145/3548606.3560678
- kstenerud 3y agoCat-and-mouse. It won't be hard to train models to recognize and compensate for this and other permutations of it. Meanwhile you've uglified your art piece.
- GaggiX 3y agoThese tools do not work in the real world for several reasons: first, people who train LoRA or models curate their datasets, removing adversarial noise is trivial: https://github.com/lllyasviel/AdverseCleaner https://github.com/lllyasviel/AdverseCleaner ; second, if they are trying to defend themselves against training AI models, then it will probably do almost nothing at all, models trained from scratch will learn the distribution, even one where the samples have adversarial noise (which can only attack a frozen model, like a VAE), SDXL has a new VAE, so the VAE will just be more robust if there is adversarial noise on the images, because it will learn to ignore it, many other models do not have a VAE to begin with. Also, resizing the image (as is almost always done when training the model) will probably destroy most if not all of the adversarial noise.
- brookst 3y agoIt’s hilarious that we all know DRM for video is doomed because anything someone can see can be copied. And yet people think that somehow visual art is different; that there must be some technical solution that will keep the wrong people/computers from being able to see it, while letting the right ones in. It is not now, and it never has been, and it never will be possible to have widespread distribution and absolute control over copies.
- hamandcheese 3y ago> It is not now, and it never has been, and it never will be possible to have widespread distribution and absolute control over copies. I sure hope this is true, but this strikes me as a bold statement given the ongoing war on general-purpose computing.
- Turskarama 3y agoEven if you went to such extreme lengths as encrypting it such that decryption happened on monitors, a camera with a high enough resolution could still just make an (imperfect) copy.
- 3y ago
- worrycue 3y agoAI has open a real big can of worms. Frankly, I see AI training on publicly available images to learn a style which it will then reproduce similar to the problem of game clones. Imagine spending months/years making a game, coming up with the concept and gameplay, tuning the gameplay, … then after release cloners makes a nigh exact copy with slight changes in artwork/text and sell it for 10% of what you are selling - which they can since they put in only a fraction of the effort - and there is nothing you can do about it since gameplay isn’t copyrightable. Same thing here IMHO. Not an AI specific problem but AI takes “no effort” when replicating an artist’s style vs a human who at least has to practice and learn the style.
- hooverd 3y agoAI art seems great if you want to generate an 80% there stream of generic waifus, but turns out nobody wants to see that. It's like buying a coffee mug from the store and wanting praise as if you fired it yourself.
- onetokeoverthe 3y agoGuess what. If an AI uses my work i'll sue. Simple as that.
- pawelmurias 3y agoHow do you plan to detect if your work was one of the thousands it used to train itself?
- onetokeoverthe 3y ago[dead]