mlsanityData to 14 Oct 2026

FreqMark: Invisible Image Watermarking via Frequency Based Optimization in Latent Space

arXiv 2410.20824 ↗First posted 28 Oct 2024cs.CR cs.CV cs.LGcited by 8

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Abstract (arXiv)

Invisible watermarking is essential for safeguarding digital content, enabling copyright protection and content authentication. However, existing watermarking methods fall short in robustness against regeneration attacks. In this paper, we propose a novel method called FreqMark that involves unconstrained optimization of the image latent frequency space obtained after VAE encoding. Specifically, FreqMark embeds the watermark by optimizing the latent frequency space of the images and then extracts the watermark through a pre-trained image encoder. This optimization allows a flexible trade-off between image quality with watermark robustness and effectively resists regeneration attacks. Experimental results demonstrate that FreqMark offers significant advantages in image quality and robustness, permits flexible selection of the encoding bit number, and achieves a bit accuracy exceeding 90% when encoding a 48-bit hidden message under various attack scenarios.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 36 of its 60 references that are in the map. First posted on arXiv 28 Oct 2024.

Builds on

36 of 60 references.

References · 36

  1. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
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  11. 2017Progressive Growing of GANs for Improved Quality, Stability, and Variationcited by 2,988
  12. 2014Conditional Generative Adversarial Netscited by 2,162
24 more
  1. 2015Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networkscited by 2,054
  2. 2021VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learningcited by 1,057
  3. 2018Variational image compression with a scale hyperpriorcited by 935
  4. 2019Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space?cited by 675
  5. 2020Learned Image Compression with Discretized Gaussian Mixture Likelihoods and Attention Modulescited by 590
  6. 2020Leveraging Frequency Analysis for Deep Fake Image Recognitioncited by 504
  7. 2018HiDDeN: Hiding Data With Deep Networkscited by 397
  8. 2022DiffusionDB: A Large-scale Prompt Gallery Dataset for Text-to-Image Generative Modelscited by 379
  9. 2023The Stable Signature: Rooting Watermarks in Latent Diffusion Modelscited by 304
  10. 2020What makes fake images detectable? Understanding properties that generalizecited by 273
  11. 2019Robust Invisible Video Watermarking with Attentioncited by 149
  12. 2023A Recipe for Watermarking Diffusion Modelscited by 141
  13. 2021Are GAN generated images easy to detect? A critical analysis of the state-of-the-artcited by 139
  14. 2021Adversarial purification with Score-based generative modelscited by 134
  15. 2023Invisible Image Watermarks Are Provably Removable Using Generative AIcited by 134
  16. 2020Adversarial Watermarking Transformer: Towards Tracing Text Provenance with Data Hidingcited by 130
  17. 2024WAVES: Benchmarking the Robustness of Image Watermarkscited by 97
  18. 2021Watermarking Images in Self-Supervised Latent Spacescited by 94
  19. 2020Responsible Disclosure of Generative Models Using Scalable Fingerprintingcited by 91
  20. 2020DeepFake Detection by Analyzing Convolutional Tracescited by 81
  21. 2023Robustness of AI-Image Detectors: Fundamental Limits and Practical Attackscited by 81
  22. 2018ReDMark: Framework for Residual Diffusion Watermarking on Deep Networkscited by 57
  23. 2023Leveraging Optimization for Adaptive Attacks on Image Watermarkscited by 52
  24. 2022Supervised GAN Watermarking for Intellectual Property Protectioncited by 40

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 5.

8 papers.

  1. 2025Semantic Watermarking Reinvented: Enhancing Robustness and Generation Quality with Fourier Integritycited by 14
  2. 2026Towards Robust Content Watermarking Against Removal and Forgery Attackscited by 3
  3. 2025Low-Compute Watermark Removal via Dual-Domain Natural Projectioncited by 1
  4. 2026PhaseMark: A Post-hoc, Optimization-Free Watermarking of AI-generated Images in the Latent Frequency Domaincited by 1
  5. 2026Off-The-Shelf Image-to-Image Models Are All You Need To Defeat Image Protection Schemescited by 1
  6. 2025Multi-bit Audio Watermarkingcited by 0
  7. 2026Correlation-Aware and Gaussianity-Preserving Robust Latent Angular Watermarking for Diffusion Modelscited by 0
  8. 2026Certification of Real Images through Calibrated Content Authenticationcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2023FreqyWM: Frequency Watermarking for the New Data Economy
  2. 2024An Undetectable Watermark for Generative Image Models
  3. 2024Invisible Watermarks: Attacks and Robustness
  4. 2026Exploring Weaknesses of Generative Image Watermarks against Latent Frequency Masking
  5. 2026DeepFreqMark: End-To-End Learnable Frequency-Domain Watermarking with Spherical Attack Simulation for Latent Diffusion Models
  6. 2026FDDWAN: A Frequency-Decoupled Diffusion Network for Watermarking Attack
  7. 2024Hidden in the Noise: Two-Stage Robust Watermarking for Images
  8. 2024LVMark: Robust Watermark for Latent Video Diffusion Models