On the Intrinsic Limited Robustness of Latent-Based Watermarking
Read the original on arXiv Machine Learning →The Flow has not summarised this story yet — read it at arXiv Machine Learning.
The Flow has not summarised this story yet — read it at arXiv Machine Learning.
arXiv:2608. 10166v1 Announce Type: cross Abstract: Digital watermarking has emerged as a critical technique for provenance and copyright attribution in AI-generated imagery, yet its robustness against realistic, model-agnostic removal attacks remains poorly explored.
The paper introduces Latent Frequency Masking, an attack that removes or weakens invisible watermarks in AI-generated images by altering selected Fourier coefficients in the latent space. It demonstrates that this method can effectively compromise six diffusion watermarking techniques while maintaining image quality and running faster than existing attacks. The study provides a theoretical distortion bound and evaluates the attack on images from DiffusionDB and MS-COCO prompts.
arXiv:2610.12952v1 Announce Type: cross Abstract: Image watermarking enables provenance tracing for photorealistic images generated by diffusion models. However, state-of-the-art (SOTA) removal attac...
arXiv:2610.03166v1 Announce Type: cross Abstract: Digital watermarking supports source attribution for AI-generated images, but its reliability depends on resistance to removal attacks. Some attacks...
4D-GSW is a kinematic-aware watermarking framework for 4D Gaussian Splatting that embeds robust copyright information while preserving high spatio-temporal consistency. It introduces a Spatio-Temporal Curvature metric to identify dynamic instants and gates watermark gradient injection, and uses a joint HMM-MRF energy minimization model to synchronize watermark phases across temporal trajectories and spatial neighborhoods. An anisotropic gradient routing mechanism ensures watermark embedding remains decoupled from photometric reconstruction fidelity, achieving superior robustness and rendering quality in experiments.
arXiv:2609.40031v1 Announce Type: cross Abstract: Digital image watermarking is increasingly critical in media contexts, as emerging regulations and industry practices require marking AI-generated co...