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PyTorch implementation of HiFiMSFA: Robust and High-Fidelity Image Watermarking using Attention Augmented Deep Network

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HiFiMSFA

Introduction

This repository is the official PyTorch implementation of HiFiMSFA: Robust and High-Fidelity Image Watermarking using Attention Augmented Deep Network. The paper proposes a deep image watermarking framework with multi-scale salient feature attention and adaptive squared Hinge loss.

Train

If you need to train HiFiMSFA, you should use commond line as following.

  python train.py

Requirements: torch == 1.10.1+cu111 torchvision == 0.11.2+cu111 kornia == 0.6.8

Test

The pre-trained model of HiFiMSFA is avaliable at the pretrain floder. you can test it by command line as following.

  python test.py

License

The models are free for non-commercial and scientific research purpose. Please mail us for further licensing terms.

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PyTorch implementation of HiFiMSFA: Robust and High-Fidelity Image Watermarking using Attention Augmented Deep Network

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