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the code of paper of EFFICIENT FUSION OF DEPTH INFORMATION FOR DEFOCUS DEBLURRING-ICASSP2024

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DEDDNet

the code of paper of EFFICIENT FUSION OF DEPTH INFORMATION FOR DEFOCUS DEBLURRING-ICASSP2024

The link to the pre-trained model of DEDDNet is: https://drive.google.com/file/d/1DnVfActIucVEVyZw0rX3Mdx7-K4mYRvt/view?usp=sharing

The link to the pre-trained model of MonoDepthV2 is: https://drive.google.com/file/d/1DH8VL_dv2dkMbcHk7v6dMlNux0ggJsOn/view?usp=sharing

After downloading the file, put the models in experiment\

monodepthmodels\

for testing, modify \option\test\Deblur_Dataset_Test.yaml for your dataset. Run test_D.py.

for training, modify \option\test\Defocus_GAN_Trained.yaml for your dataset. And then you can use train_finalD.py for training

Acknowledgement

We acknowledge the researcher of MDPNet, DPDDNet, BaMBNet.

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the code of paper of EFFICIENT FUSION OF DEPTH INFORMATION FOR DEFOCUS DEBLURRING-ICASSP2024

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