mlsanityData to 7 Oct 2026

A Somewhat Robust Image Watermark against Diffusion-based Editing Models

arXiv 2311.13713 ↗First posted 22 Nov 2023cs.CR cs.CV cs.LGcited by 4

On the map: Diffusion models → Robustness, privacy and adversarial aspects

also in 1 more
Abstract (arXiv)

Recently, diffusion models (DMs) have become the state-of-the-art method for image synthesis. Editing models based on DMs, known for their high fidelity and precision, have inadvertently introduced new challenges related to image copyright infringement and malicious editing. Our work is the first to formalize and address this issue. After assessing and attempting to enhance traditional image watermarking techniques, we recognize their limitations in this emerging context. In response, we develop a novel technique, RIW (Robust Invisible Watermarking), to embed invisible watermarks leveraging adversarial example techniques. Our technique ensures a high extraction accuracy of 96% for the invisible watermark after editing, compared to the 0% offered by conventional methods. We provide access to our code at https://github.com/BennyTMT/RIW.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Placed in Robustness, privacy and adversarial aspects, one of 14 directions in Diffusion models. Builds on 59 of its 65 references that are in the map. First posted on arXiv 22 Nov 2023.

Builds on

59 of 65 references.

Closest ancestors · 7

Same direction, newest first

  1. 2023EditShield: Protecting Unauthorized Image Editing by Instruction-guided Diffusion Models19 Nov
  2. 2023Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust31 May
  3. 2023DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models25 May
  4. 2023Mist: Towards Improved Adversarial Examples for Diffusion Models22 May
  5. 2023Watermarking Diffusion Model21 May
  6. 2023A Recipe for Watermarking Diffusion Models17 Mar
  7. 2023Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples9 Feb

Other references · 52

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  4. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  5. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  6. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
  7. 2020Denoising Diffusion Implicit Modelscited by 9,655
  8. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  9. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  10. 2014Explaining and Harnessing Adversarial Examplescited by 7,287
  11. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  12. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
38 more
  1. 2017Towards Deep Learning Models Resistant to Adversarial Attackscited by 6,326
  2. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  3. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 5,986
  4. 2022Classifier-Free Diffusion Guidancecited by 5,717
  5. 2017mixup: Beyond Empirical Risk Minimizationcited by 5,155
  6. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,510
  7. 2021Zero-Shot Text-to-Image Generationcited by 4,276
  8. 2022LAION-5B: An open large-scale dataset for training next generation image-text modelscited by 4,131
  9. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  10. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,595
  11. 2022DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generationcited by 3,286
  12. 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,006
  13. 2015FaceNet: A Unified Embedding for Face Recognition and Clusteringcited by 2,833
  14. 2022InstructPix2Pix: Learning to Follow Image Editing Instructionscited by 2,591
  15. 2022Prompt-to-Prompt Image Editing with Cross Attention Controlcited by 2,409
  16. 2021SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equationscited by 1,903
  17. 2022Make-A-Video: Text-to-Video Generation without Text-Video Datacited by 1,725
  18. 2021Image Super-Resolution via Iterative Refinementcited by 1,506
  19. 2023Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Modelscited by 1,465
  20. 2020DiffWave: A Versatile Diffusion Model for Audio Synthesiscited by 1,339
  21. 2022Imagic: Text-Based Real Image Editing with Diffusion Modelscited by 1,172
  22. 2021Cascaded Diffusion Models for High Fidelity Image Generationcited by 1,155
  23. 2017BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chaincited by 1,052
  24. 2021Blended Diffusion for Text-driven Editing of Natural Imagescited by 924
  25. 2022eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoiserscited by 921
  26. 2021Multi-Stage Progressive Image Restorationcited by 813
  27. 2018Multimodal Unsupervised Image-to-Image Translationcited by 795
  28. 2019Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space?cited by 675
  29. 2018Mitigating Unwanted Biases with Adversarial Learningcited by 663
  30. 2019Image2StyleGAN++: How to Edit the Embedded Images?cited by 356
  31. 2019Few-Shot Unsupervised Image-to-Image Translationcited by 222
  32. 2022Dual Diffusion Implicit Bridges for Image-to-Image Translationcited by 212
  33. 2020Artificial Fingerprinting for Generative Models: Rooting Deepfake Attribution in Training Datacited by 200
  34. 2023Glaze: Protecting Artists from Style Mimicry by Text-to-Image Modelscited by 200
  35. 2019Robust Invisible Video Watermarking with Attentioncited by 144
  36. 2023Invisible Image Watermarks Are Provably Removable Using Generative AIcited by 124
  37. 2023Evading Watermark based Detection of AI-Generated Contentcited by 74
  38. 2023Leveraging Optimization for Adaptive Attacks on Image Watermarkscited by 50

50 most cited of 52 All 52 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 1; 2026: 1.

4 papers.

  1. 2024TabularMark: Watermarking Tabular Datasets for Machine Learningcited by 8
  2. 2024U Can't Gen This? A Survey of Intellectual Property Protection Methods for Data in Generative AIcited by 7
  3. 2025Beyond Vulnerabilities: A Survey of Adversarial Attacks as Both Threats and Defenses in Computer Vision Systemscited by 4
  4. 2026Trustworthy synthetic visual media: Evidence across the media lifecyclecited by 0

Similar, not cited

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  3. 2026Vanishing Watermarks: Diffusion-Based Image Editing Undermines Robust Invisible Watermarking
  4. 2024ROBIN: Robust and Invisible Watermarks for Diffusion Models with Adversarial Optimization
  5. 2025On the Information-Theoretic Fragility of Robust Watermarking under Diffusion Editing
  6. 2024Watermark-embedded Adversarial Examples for Copyright Protection against Diffusion Models
  7. 2025Diffusion-Based Image Editing for Breaking Robust Watermarks
  8. 2024An Undetectable Watermark for Generative Image Models