AI RESEARCH

Understanding Semantic Perturbations on In-Processing Generative Image Watermarks

arXiv CS.AI

ArXi:2603.27513v1 Announce Type: cross The widespread deployment of high-fidelity generative models has intensified the need for reliable mechanisms for provenance and content authentication. In-processing watermarking, embedding a signature into the generative model's synthesis procedure, has been advocated as a solution and is often reported to be robust to standard post-processing (such as geometric transforms and filtering). Yet robustness to semantic manipulations that alter high-level scene content while maintaining reasonable visual quality is not well studied or understood. We.