# DPSR **Repository Path**: wangchsoft/DPSR ## Basic Information - **Project Name**: DPSR - **Description**: No description available - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2020-11-09 - **Last Updated**: 2020-12-19 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # DPSR # Deep Plug-and-Play Super-Resolution for Arbitrary Blur Kernels (CVPR, 2019) - Related work: [DPIR](https://github.com/cszn/DPIR) # Training and testing codes for the super-resolver prior ([PyTorch](https://github.com/cszn/KAIR)) - [main_train_dpsr.py](https://github.com/cszn/KAIR/blob/master/main_train_dpsr.py) - [main_test_dpsr.py](https://github.com/cszn/KAIR/blob/master/main_test_dpsr.py) *** The left is the blurry LR image. The right is the super-resolved image by DPSRGAN with scale factor 4. Run [demo_test_dpsr.py](demo_test_dpsr.py) to produce the following results. *** Super-resolved images of LR image [chip.png](testsets/real_imgs/LR/chip.png) by DPSR with scale factors 2, 3 and 4. Run [demo_test_dpsr_real.py](demo_test_dpsr_real.py) to produce the following results. LR x2 x3 x4 # Requirements and Dependencies - Spyder (Python 3.6) - PyTorch 0.4.1 - Windows 10 # Citation ```BibTex @inproceedings{zhang2019deep, title={Deep Plug-and-Play Super-Resolution for Arbitrary Blur Kernels}, author={Zhang, Kai and Zuo, Wangmeng and Zhang, Lei}, booktitle={IEEE Conference on Computer Vision and Pattern Recognition}, pages={1671--1681}, year={2019} } ```