SWIFT: Semantic Watermarking for Image Forgery Thwarting
<|reference_start|>SWIFT: Semantic Watermarking for Image Forgery Thwarting: 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.<|reference_end|>
@article{evennou2024swift:,
    title={SWIFT: Semantic Watermarking for Image Forgery Thwarting},
    author={Gautier Evennou, Vivien Chappelier, Ewa Kijak and Teddy Furon},
    journal={arXiv preprint arXiv:2407.18995},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.18995},
    primaryClass={cs.CR cs.AI cs.CV cs.MM}
}