On the Intrinsic Limited Robustness of Latent-Based Watermarking
Researchers argue latent diffusion watermarks are intrinsically fragile to rotation, scaling, and translation.
A theoretical analysis argues that latent-based watermarking for diffusion models overestimates robustness to geometric distortions such as rotation, scaling, and translation. The authors relax invariance assumptions to derive a maximum perturbation bound linking pixel-space changes to latent-space effects, and give an analytical formulation of practical detection. Experiments support the claim that, under the current design paradigm, these watermarks have inherent robustness limits, and the paper offers design guidelines for future work.
- Latent watermarks lack invariance to rotation, scaling, and translation.
- A bound links pixel-space perturbations to effects in latent space.
- Authors formulate practical detection and validate the limits experimentally.
- Current latent watermark designs are argued to be intrinsically limited.
From the original article
1 min read at arxiv.orgExisting 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.
By Cheng-Han Yeh · arxiv.org
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