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Deep Stacked Multi-patch Hierarchical Network for Image Deblurring

Pytorch Implementation of CVPR19 "Deep Stacked Multi-patch Hierarchical Network for Image Deblurring" <br/>

Please download GoPro dataset into './datas'. <br/> https://drive.google.com/file/d/1H0PIXvJH4c40pk7ou6nAwoxuR4Qh_Sa2/view

GoPro Pretrained models are stored in './checkpoints'.

Requires.

pytorch-0.4.1
numpy
scipy
scikit-image

For model training, run following commands.

python xxx.py -b 6

For model testing, copy test samples into './test_samples', then run following commands.

python xxx_test.py

Citation

If you think this work is useful for your research, please cite the following papers.

Conference Version:

@InProceedings{Zhang_2019_CVPR,
    author = {Zhang, Hongguang and Dai, Yuchao and Li, Hongdong and Koniusz, Piotr},
    title = {Deep Stacked Hierarchical Multi-Patch Network for Image Deblurring},
    booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
    month = {June},
    year = {2019}
}

Journal Version:

@article{zhang2022event,
    title={Event-guided Multi-patch Network with Self-supervision for Non-uniform Motion Deblurring},
    author={Zhang, Hongguang and Zhang, Limeng and Dai, Yuchao and Li, Hongdong and Koniusz, Piotr},
    journal={International Journal of Computer Vision},
    pages={1--18},
    year={2022},
    publisher={Springer}}