mlsanityData to 7 Oct 2026

DiffuseTrace: A Transparent and Flexible Watermarking Scheme for Latent Diffusion Model

arXiv 2405.02696 ↗First posted 4 May 2024cs.CR cs.AIcited by 21

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

also in 1 more
Abstract (arXiv)

Latent Diffusion Models (LDMs) enable a wide range of applications but raise ethical concerns regarding illegal utilization. Adding watermarks to generative model outputs is a vital technique employed for copyright tracking and mitigating potential risks associated with Artificial Intelligence (AI)-generated contents. However, post-processed watermarking methods are unable to withstand generative watermark attacks and there exists a trade-off between image fidelity and watermark strength. Therefore, we propose a novel technique called DiffuseTrace. DiffuseTrace does not rely on fine-tuning of the diffusion model components. The multi-bit watermark is a embedded into the image space semantically without compromising image quality. The watermark component can be utilized as a plug-in in arbitrary diffusion models. We validate through experiments the effectiveness and flexibility of DiffuseTrace. Under 8 types of image processing watermark attacks and 3 types of generative watermark attacks, DiffuseTrace maintains watermark detection rate of 99% and attribution accuracy of over 94%.

Key facts. Cited by 21 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 40 of its 50 references that are in the map. First posted on arXiv 4 May 2024.

Builds on

40 of 50 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 · 37

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  3. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  4. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  5. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  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. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  11. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  12. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
25 more
  1. 2021Zero-Shot Text-to-Image Generationcited by 4,276
  2. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,595
  3. 2020Taming Transformers for High-Resolution Image Synthesiscited by 3,229
  4. 2022InstructPix2Pix: Learning to Follow Image Editing Instructionscited by 2,591
  5. 2022Imagen Video: High Definition Video Generation with Diffusion Modelscited by 1,765
  6. 2021Image Super-Resolution via Iterative Refinementcited by 1,506
  7. 2023Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Modelscited by 1,465
  8. 2022RePaint: Inpainting using Denoising Diffusion Probabilistic Modelscited by 1,419
  9. 2021Palette: Image-to-Image Diffusion Modelscited by 1,296
  10. 2022Null-text Inversion for Editing Real Images using Guided Diffusion Modelscited by 1,168
  11. 2022DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Modelscited by 924
  12. 2018Variational image compression with a scale hyperpriorcited by 910
  13. 2019CNN-generated images are surprisingly easy to spot... for nowcited by 842
  14. 2020Learned Image Compression with Discretized Gaussian Mixture Likelihoods and Attention Modulescited by 570
  15. 2020Leveraging Frequency Analysis for Deep Fake Image Recognitioncited by 501
  16. 2016Tutorial on Variational Autoencoderscited by 404
  17. 2023DIRE for Diffusion-Generated Image Detectioncited by 386
  18. 2018HiDDeN: Hiding Data With Deep Networkscited by 384
  19. 2022DiffusionDB: A Large-scale Prompt Gallery Dataset for Text-to-Image Generative Modelscited by 376
  20. 2019StegaStamp: Invisible Hyperlinks in Physical Photographscited by 256
  21. 2019Robust Invisible Video Watermarking with Attentioncited by 144
  22. 2023Invisible Image Watermarks Are Provably Removable Using Generative AIcited by 124
  23. 2021Watermarking Images in Self-Supervised Latent Spacescited by 90
  24. 2023On Exact Inversion of DPM-Solverscited by 47
  25. 2020Autoencoding Variational Autoencodercited by 24

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 7; 2025: 7; 2026: 7.

21 papers.

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  1. 2024Watermark Anything with Localized Messagescited by 49
  2. 2024WMAdapter: Adding WaterMark Control to Latent Diffusion Modelscited by 29
  3. 2024SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Modelscited by 26
  4. 2024Steganalysis on Digital Watermarking: Is Your Defense Truly Impervious?cited by 10
  5. 2025Safe-Sora: Safe Text-to-Video Generation via Graphical Watermarkingcited by 9
  6. 2024SuperMark: Robust and Training-free Image Watermarking via Diffusion-based Super-Resolutioncited by 4
  7. 2025GaussianSeal: Rooting Adaptive Watermarks for 3D Gaussian Generation Modelcited by 4
  8. 2025Safe-VAR: Safe Visual Autoregressive Model for Text-to-Image Generative Watermarkingcited by 4
  9. 2026Cert-LAS: Toward Certified Model Ownership Verification for Text-to-Image Diffusion Models via Layer-Adaptive Smoothingcited by 3
  10. 2024SAT-LDM: Provably Generalizable Image Watermarking for Latent Diffusion Models with Self-Augmented Trainingcited by 2
  11. 2025PT-Mark: Invisible Watermarking for Text-to-image Diffusion Models via Semantic-aware Pivotal Tuningcited by 2
  12. 2026Learning to Watermark in the Latent Space of Generative Modelscited by 2
9 more
  1. 2025SWA-LDM: Toward Stealthy Watermarks for Latent Diffusion Modelscited by 1
  2. 2025PCDiff: Proactive Control for Ownership Protection in Diffusion Models with Watermark Compatibilitycited by 1
  3. 2025WaterFlow: Learning Fast & Robust Watermarks using Stable Diffusioncited by 1
  4. 2024Embedding Watermarks in Diffusion Process for Model Intellectual Property Protectioncited by 0
  5. 2026VTONGuard: Automatic Detection and Authentication of AI-Generated Virtual Try-On Contentcited by 0
  6. 2026Proof-of-Authorship for Diffusion-based AI Generated Contentcited by 0
  7. 2026FedOT: Ownership Verification and Leakage Tracing via Watermarks for Federated LDMscited by 0
  8. 2026Position: AI/ML Deepfake Research is Misaligned with AI-Generated Non-Consensual Intimate Imagery (AIG-NCII)cited by 0
  9. 2026Diffusion-Generated Image Watermarking: A Two-Axis Taxonomy and Three Protocol-Bounded Case Studiescited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024Shallow Diffuse: Robust and Invisible Watermarking through Low-Dimensional Subspaces in Diffusion Models
  2. 2025Visual Watermarking in the Era of Diffusion Models: Advances and Challenges
  3. 2025Image Watermarking of Generative Diffusion Models
  4. 2025TraceMark-LDM: Authenticatable Watermarking for Latent Diffusion Models via Binary-Guided Rearrangement
  5. 2025Secure and Efficient Watermarking for Latent Diffusion Models in Model Distribution Scenarios
  6. 2023DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models
  7. 2025MarkDiffusion: An Open-Source Toolkit for Generative Watermarking of Latent Diffusion Models
  8. 2025Guidance Watermarking for Diffusion Models