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arXiv:2212.03860cs.LG

Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Models

Gowthami Somepalli, Vasu Singla, Micah Goldblum, Jonas Geiping, Tom Goldstein

Abstract

Cutting-edge diffusion models produce images with high quality and customizability, enabling them to be used for commercial art and graphic design purposes. But do diffusion models create unique works of art, or are they replicating content directly from their training sets? In this work, we study image retrieval frameworks that enable us to compare generated images with training samples and detect when content has been replicated. Applying our frameworks to diffusion models trained on multiple datasets including Oxford flowers, Celeb-A, ImageNet, and LAION, we discuss how factors such as training set size impact rates of content replication. We also identify cases where diffusion models, including the popular Stable Diffusion model, blatantly copy from their training data.

arXiv comments
Updated draft with the following changes (1) Clarified the LAION Aesthetics versions everywhere (2) Correction on which LAION Aesthetics version SD - 1.4 is finetuned on and updated figure 12 based on this (3) A section on possible causes of replication
Journal reference
DOI
Subjects
cs.LGMachine Learning cs.CVComputer Vision and Pattern Recognition cs.CYComputers and Society

On Hacker News

Linked by 10 identifiable commenters in 11 comments across 8 threads, from Dec 2022 to Jul 2024. Found in 3 HN submissions from Dec 2022 to Dec 2022. Open submission discussions.

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Discussed in comments8 threads

  1. Brazil data regulator bans Meta from mining data to train AI models 1 comment

    • what are the opinions on [0]? what's the scene for language rather than image? also what are the opinions on turning generative AI (that doesn't ask permission to creators) public domain? donation money that surpasses the cost of hosting the work to people/groups "creating" with…

      luqtasView on HNParent context

  2. Stable Attribution 2 comments

    • I do want to clarify that I think stable diffusion and tools like it can engage in illegal copying. For example it will happily produce infringing images of logos and even somewhat random other images https://arxiv.org/pdf/2212.03860.pdf. It seems like it’s devoting an uneven…

      space_fountainView on HNParent context

    • is this (1) the lawsuit you're referring to? 'cause those images are not the same. Sports events are just easy to fake, because they're boring - all sports pictures look roughly the same. Edited to add: There's another lawsuit (a class action - 2), and after a little light…

      pksebbenView on HNParent context

  3. Extracting training data from diffusion models 1 comment

    • Also another previous study that has Stable Diffusion (SD) emitting images in the training set [0] It is now clear that SD is treading on thin ice: training on watermarked and copyrighted images without their author's permission, then attempting to commercialize it even when the…

      rvzView on HNParent context

  4. An IP attorney’s reading of the Stable Diffusion class action lawsuit 1 comment

    • Afaik theoretically you could reproduce any image in the training set using the full weights (not a fraction of them) and the correct prompt. In practice since this is an extremely lossy process, some or most of them aren't reproducible. For this specific case, I suspect it'll…

      N1ckFGView on HNParent context

  5. AI is in danger of being swallowed up by copyright law 1 comment

    • Honestly, can people stop speaking in absolutes regarding these systems? We (researchers and non-researchers alike) are gradually trying to comprehend exactly how much they generalise and memorise, but this is darn hard work and it is not our fault that several major tech giants…

      ninjinView on HNParent context

  6. Stable Diffusion Frivolous Litigation 1 comment

    • > Could you provide evidence of your last statement? I haven’t seen these models produce actual copies of any art (can’t imagine that’s an option in general). Here's a whole paper, complete with citations: https://arxiv.org/pdf/2212.03860.pdf > These models do not contain…

      karpierzView on HNParent context

  7. We’ve filed a law­suit chal­leng­ing Sta­ble Dif­fu­sion 3 comments

    • There is no need for rhetorical games. The actual issue is that Stable Diffusion does create derivatives of copyrighted works. In some cases the produced images contain pixel level details from the originals. [1] [1] https://arxiv.org/pdf/2212.03860.pdf

      IncRndView on HNParent context

    • > The actual issue is that Stable Diffusion does create derivatives of copyrighted works. Nothing points to that, in fact even in this website they had to lie on how stablediffusion actually works, maybe a sign that their argument isn't really solid enough. > [1]…

      realusernameView on HNParent context

    • > when doing paintovers on copyrighted images (VERY common) What are you talking about? I've been doing drawing and digital painting as a hobby for a long time and tracing is absolutely not "VERY common". I don't know anybody who has ever done this. > fan art where they paint…

      zowie_vdView on HNParent context

  8. GPT3/DALL-E2 in Discord, chat like ChatGPT, generate images, and more 1 comment

    • From fact checking myself it is worth noting that stable diffusion will absolutely copy things in ways that would probably infringe a copyright (not a layer and not legal advice), but I found this paper interesting both because some of the examples it gives of clear copying…

      space_fountainView on HNParent context

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