DMPHN-cvpr19 论文代码

# Deep Stacked Multi-patch Hierarchical Network for Image Deblurring Pytorch Implementation of CVPR19 "[Deep Stacked Multi-patch Hierarchical Network for Image Deblurring](https://arxiv.org/pdf/1904.03468.pdf)" <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}} ```