This paper proposes a novel approach towards image authentication and tampering detection by using watermarking as a communication channel for semantic information. We modify the HiDDeN deep-learning watermarking architecture to embed and extract high-dimensional real vectors representing image captions. Our method improves significantly robustness on both malign and benign edits. We also introduce a local confidence metric correlated with Message Recovery Rate, enhancing the method's practical applicability. This approach bridges the gap between traditional watermarking and passive forensic methods, offering a robust solution for image integrity verification.
@article{arxiv.2407.18995,
title = {SWIFT: Semantic Watermarking for Image Forgery Thwarting},
author = {Gautier Evennou and Vivien Chappelier and Ewa Kijak and Teddy Furon},
journal= {arXiv preprint arXiv:2407.18995},
year = {2025}
}
Comments
Accepted at IEEE WIFS 2024; Code released at : https://github.com/gautierevn/swift_watermarking