On the Intrinsic Limited Robustness of Latent-Based Watermarking
Existing latent-based watermarking methods for diffusion models have overestimated their robustness to image distortions, including geometric transformations such as rotation, scaling, and translation (RST).
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Key points
- Moreover, this paradigm of watermarking approaches may suffer from inherent limitations arising from the domain in which the watermark is embedded.
- In this paper, we provide the first theoretical analysis explaining why these methods lack invariance to perturbations.
- By relaxing the invariant relation, we derive a maximum perturbation bound that characterizes the relationship between pixel-space perturbations and their corresponding effects in latent space.
- Our theoretical and empirical results indicate that, under the current design paradigm, latent-based watermarking methods intrinsically exhibit limited robustness.
Sources (1)
- [1]On the Intrinsic Limited Robustness of Latent-Based WatermarkingarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 6, 11:29 AM
Existing latent-based watermarking methods for diffusion models have overestimated their robustness to image distortions, including geometric transformations such as rotation, scaling, and translation (RST).
Moreover, this paradigm of watermarking approaches may suffer from inherent limitations arising from the domain in which the watermark is embedded.
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