SWIFT: Semantic Watermarking for Image Forgery Thwarting

• URL: http://arxiv.org/abs/2407.18995v1
• Date: Fri, 26 Jul 2024 09:50:13 GMT
• Title: SWIFT: Semantic Watermarking for Image Forgery Thwarting
• Authors: Gautier Evennou, Vivien Chappelier, Ewa Kijak, Teddy Furon,
• Abstract summary: We modify the HiDDeN deep-learning watermarking architecture to embed and extract high-dimensional real vectors representing image captions. Our method improves significantly on both malign and benign edits.
• Score: 12.515429388063534
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: 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.

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