Deep Boosting Robustness of DNN-based Image Watermarking via DBMark

• URL: http://arxiv.org/abs/2210.13801v2
• Date: Wed, 26 Oct 2022 03:48:23 GMT
• Title: Deep Boosting Robustness of DNN-based Image Watermarking via DBMark
• Authors: Guanhui Ye, Jiashi Gao, Wei Xie, Bo Yin, Xuetao Wei
• Abstract summary: We present DBMark, a new end-to-end digital image watermarking framework to boost the robustness of DNN-based image watermarking. The framework generates watermark features with redundancy and error correction ability through message processing, synergized with the powerful information embedding and extraction capabilities of Invertible Neural Networks.
• Score: 3.9394166162483835
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this paper, we present DBMark, a new end-to-end digital image watermarking framework to deep boost the robustness of DNN-based image watermarking. The key novelty is the synergy of the Invertible Neural Networks(INNs) and effective watermark features generation. The framework generates watermark features with redundancy and error correction ability through message processing, synergized with the powerful information embedding and extraction capabilities of Invertible Neural Networks to achieve higher robustness and invisibility. Extensive experiment results demonstrate the superiority of the proposed framework compared with the state-of-the-art ones under various distortions.

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