mlsanityData to 7 Oct 2026

WOUAF: Weight Modulation for User Attribution and Fingerprinting in Text-to-Image Diffusion Models

arXiv 2306.04744 ↗First posted 7 Jun 2023cs.CVcited by 51

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

Abstract (arXiv)

The rapid advancement of generative models, facilitating the creation of hyper-realistic images from textual descriptions, has concurrently escalated critical societal concerns such as misinformation. Although providing some mitigation, traditional fingerprinting mechanisms fall short in attributing responsibility for the malicious use of synthetic images. This paper introduces a novel approach to model fingerprinting that assigns responsibility for the generated images, thereby serving as a potential countermeasure to model misuse. Our method modifies generative models based on each user's unique digital fingerprint, imprinting a unique identifier onto the resultant content that can be traced back to the user. This approach, incorporating fine-tuning into Text-to-Image (T2I) tasks using the Stable Diffusion Model, demonstrates near-perfect attribution accuracy with a minimal impact on output quality. Through extensive evaluation, we show that our method outperforms baseline methods with an average improvement of 11% in handling image post-processes. Our method presents a promising and novel avenue for accountable model distribution and responsible use. Our code is available in urlhttps://github.com/kylemin/WOUAF.

Key facts. Cited by 51 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 43 of its 61 references that are in the map. First posted on arXiv 7 Jun 2023.

Builds on

43 of 61 references.

Closest ancestors · 3

Same direction, newest first

  1. 2023Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust31 May
  2. 2023The Stable Signature: Rooting Watermarks in Latent Diffusion Models27 Mar
  3. 2023A Recipe for Watermarking Diffusion Models17 Mar

Other references · 40

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  3. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  4. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  5. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
  6. 2020Denoising Diffusion Implicit Modelscited by 9,655
  7. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  8. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  9. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 5,986
  10. 2022Classifier-Free Diffusion Guidancecited by 5,717
  11. 2022LAION-5B: An open large-scale dataset for training next generation image-text modelscited by 4,131
  12. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,595
28 more
  1. 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,580
  2. 2020Taming Transformers for High-Resolution Image Synthesiscited by 3,229
  3. 2022Elucidating the Design Space of Diffusion-Based Generative Modelscited by 2,994
  4. 2017Progressive Growing of GANs for Improved Quality, Stability, and Variationcited by 2,967
  5. 2021CLIPScore: A Reference-free Evaluation Metric for Image Captioningcited by 2,388
  6. 2022An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversioncited by 2,231
  7. 2020Training Generative Adversarial Networks with Limited Datacited by 1,184
  8. 2018Variational image compression with a scale hyperpriorcited by 910
  9. 2019CNN-generated images are surprisingly easy to spot... for nowcited by 842
  10. 2023GLIGEN: Open-Set Grounded Text-to-Image Generationcited by 774
  11. 2023Attend-and-Excite: Attention-Based Semantic Guidance for Text-to-Image Diffusion Modelscited by 696
  12. 2018Joint Autoregressive and Hierarchical Priors for Learned Image Compressioncited by 642
  13. 2020Learned Image Compression with Discretized Gaussian Mixture Likelihoods and Attention Modulescited by 570
  14. 2018HiDDeN: Hiding Data With Deep Networkscited by 384
  15. 2018Turning Your Weakness Into a Strength: Watermarking Deep Neural Networks by Backdooringcited by 334
  16. 2023Training-Free Layout Control with Cross-Attention Guidancecited by 312
  17. 2020Watch your Up-Convolution: CNN Based Generative Deep Neural Networks are Failing to Reproduce Spectral Distributionscited by 278
  18. 2019StegaStamp: Invisible Hyperlinks in Physical Photographscited by 256
  19. 2019Kornia: an Open Source Differentiable Computer Vision Library for PyTorchcited by 231
  20. 2017Embedding Watermarks into Deep Neural Networkscited by 227
  21. 2023SnapFusion: Text-to-Image Diffusion Model on Mobile Devices within Two Secondscited by 227
  22. 2020Artificial Fingerprinting for Generative Models: Rooting Deepfake Attribution in Training Datacited by 200
  23. 2019Robust Invisible Video Watermarking with Attentioncited by 144
  24. 2020Responsible Disclosure of Generative Models Using Scalable Fingerprintingcited by 90
  25. 2021A survey of deep neural network watermarking techniquescited by 69
  26. 2021Protecting Intellectual Property of Generative Adversarial Networks from Ambiguity Attackcited by 45
  27. 2023Attributing Image Generative Models using Latent Fingerprintscited by 20
  28. 2020Decentralized Attribution of Generative Modelscited by 16

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 5; 2024: 16; 2025: 17; 2026: 13.

51 papers.

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  1. 2024Proactive Detection of Voice Cloning with Localized Watermarkingcited by 67
  2. 2024R.A.C.E.: Robust Adversarial Concept Erasure for Secure Text-to-Image Diffusion Modelcited by 56
  3. 2024λ-ECLIPSE: Multi-Concept Personalized Text-to-Image Diffusion Models by Leveraging CLIP Latent Spacecited by 51
  4. 2024Watermark Anything with Localized Messagescited by 49
  5. 2024Video Seal: Open and Efficient Video Watermarkingcited by 45
  6. 2024Fake or JPEG? Revealing Common Biases in Generated Image Detection Datasetscited by 43
  7. 2024Steering Rectified Flow Models in the Vector Field for Controlled Image Generationcited by 38
  8. 2024Copyright Protection in Generative AI: A Technical Perspectivecited by 35
  9. 2024WMAdapter: Adding WaterMark Control to Latent Diffusion Modelscited by 29
  10. 2024SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Modelscited by 26
  11. 2023ECLIPSE: A Resource-Efficient Text-to-Image Prior for Image Generationscited by 24
  12. 2023Functional Invariants to Watermark Large Transformerscited by 14
38 more
  1. 2025Pixel Seal: Adversarial-only training for invisible image and video watermarkingcited by 14
  2. 2025SEAL: Semantic Aware Image Watermarkingcited by 13
  3. 2024A Survey of Defenses Against AI-Generated Visual Media: Detection,Disruption, and Authenticationcited by 12
  4. 2023Wide Flat Minimum Watermarking for Robust Ownership Verification of GANscited by 10
  5. 2025A Comprehensive Survey on Concept Erasure in Text-to-Image Diffusion Modelscited by 9
  6. 2024LVMark: Robust Watermark for Latent Video Diffusion Modelscited by 8
  7. 2025EraseFlow: Learning Concept Erasure Policies via GFlowNet-Driven Alignmentcited by 8
  8. 2024RAW: A Robust and Agile Plug-and-Play Watermark Framework for AI-Generated Images with Provable Guaranteescited by 7
  9. 2024MarkPlugger: Generalizable Watermark Framework for Latent Diffusion Models without Retrainingcited by 5
  10. 2026SLICE: Semantic Latent Injection via Compartmentalized Embedding for Image Watermarkingcited by 5
  11. 2025GaussianSeal: Rooting Adaptive Watermarks for 3D Gaussian Generation Modelcited by 4
  12. 2025Safe-VAR: Safe Visual Autoregressive Model for Text-to-Image Generative Watermarkingcited by 4
  13. 2025StableGuard: Towards Unified Copyright Protection and Tamper Localization in Latent Diffusion Modelscited by 4
  14. 2023CopyScope: Model-level Copyright Infringement Quantification in the Diffusion Workflowcited by 3
  15. 2024Protect-Your-IP: Scalable Source-Tracing and Attribution against Personalized Generationcited by 3
  16. 2025Video Signature: Implicit Watermarking for Video Diffusion Modelscited by 3
  17. 2025AMCR: A Framework for Assessing and Mitigating Copyright Risks in Generative Modelscited by 3
  18. 2023Stable Messenger: Steganography for Message-Concealed Image Generationcited by 2
  19. 2024SAT-LDM: Provably Generalizable Image Watermarking for Latent Diffusion Models with Self-Augmented Trainingcited by 2
  20. 2025SPDMark: Selective Parameter Displacement for Robust Video Watermarkingcited by 2
  21. 2026Learning to Watermark in the Latent Space of Generative Modelscited by 2
  22. 2025Spread them Apart: Towards Robust Watermarking of Generated Contentcited by 1
  23. 2025MetaSeal: Defending Against Image Attribution Forgery Through Content-Dependent Cryptographic Watermarkscited by 1
  24. 2025Of-SemWat: High-payload text embedding for semantic watermarking of AI-generated images with arbitrary sizecited by 1
  25. 2026Off-The-Shelf Image-to-Image Models Are All You Need To Defeat Image Protection Schemescited by 1
  26. 2026Are Watermarked Images Editable? SafeMark for Watermark-Preserving Text-Guided Image Editingcited by 1
  27. 2026Data Provenance for Image Auto-Regressive Generationcited by 1
  28. 2025PALADIN : Robust Neural Fingerprinting for Text-to-Image Diffusion Modelscited by 0
  29. 2025LAID: Lightweight AI-Generated Image Detection in Spatial and Spectral Domainscited by 0
  30. 2025Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformerscited by 0
  31. 2025MOLM: Mixture of LoRA Markerscited by 0
  32. 2026Identifying Models Behind Text-to-Image Leaderboardscited by 0
  33. 2026Q-Tag: Watermarking Quantum Circuit Generative Modelscited by 0
  34. 2026Gaussian Shannon: High-Precision Diffusion Model Watermarking Based on Communicationcited by 0
  35. 2026Efficient, Robust, and Anti-Collusion Fingerprinting of Image Diffusion Modelscited by 0
  36. 2026DNA: Dual-stage Native Attribution for Generated Image Source Tracingcited by 0
  37. 2026MarkNull: Model-Agnostic Watermark Removal in AI-Generated Images via On-Manifold Latent Manipulationcited by 0
  38. 2026An Efficient and Effective Watermarking Scheme for the Protection of the Intellectual Property Rights of Video Generative Modelscited by 0

50 most cited of 51 All 51 (JSON)

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  1. 2026Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation
  2. 2025Causal Fingerprints of AI Generative Models
  3. 2022DE-FAKE: Detection and Attribution of Fake Images Generated by Text-to-Image Generation Models
  4. 2025Can Generative Models Actually Forge Realistic Identity Documents?
  5. 2024EnTruth: Enhancing the Traceability of Unauthorized Dataset Usage in Text-to-image Diffusion Models with Minimal and Robust Alterations
  6. 2024Towards Effective User Attribution for Latent Diffusion Models via Watermark-Informed Blending
  7. 2024Detecting Origin Attribution for Text-to-Image Diffusion Models
  8. 2023DIAGNOSIS: Detecting Unauthorized Data Usages in Text-to-image Diffusion Models