Watermarking security: theory and practice

By François Cayre, Caroline Fontaine, Teddy Furon. IEEE Transactions on Signal Processing, 2005

350 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Signal Processing

View Paper: https://www.semanticscholar.org/paper/1eb06efe8b13550bd7796b79c57fa25052634cea

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Ning Yu
2. Sahar Abdelnabi
3. Vladislav Skripniuk
4. Mario Fritz
5. Terrence J. Moore
6. Trevor Darrell
7. Luc Van Gool
8. Bernt Schiele

In Signal Processing

1. Mario Fritz
2. Ning Yu
3. Terrence J. Moore

Citations in the corpus

• Radioactive data: tracing through training (2020, neutral): “Although it is not the core topic of our paper, our method incidentally offers a way to watermark images in the classical sense (Cayre et al., 2005).”
• Artificial Fingerprinting for Generative Models: Rooting Deepfake Attribution in Training Data (2020, methodology): “Previous techniques rely on Fourier transform [11, 7], JPEG compression [2, 1], or least significant bits modification [38, 21, 22].”
• A Theory of Cramer-Rao Bounds for Constrained Parametric Models (2010, methodology): “The CCRB has proven useful as a performance analysis tool in localization [6], watermarking security [15], tomography [28], source bearing and symbol estimation [59], space-time block coding [42], and even a variant of least squares [46].”