SESR
SESR: Single Image Super Resolution with Recursive Squeeze and Excitation Networks (To appear in ICPR 2018)
https://arxiv.org/abs/1801.10319
Quality for scale x4
Trained on div2k, r=4
DataSet/Method |
PSNR/SSIM |
Set5 |
32.05/ 0.897 |
Set14 |
28.54/ 0.789 |
BSD100 |
27.51/ 0.743 |
Urban100 |
25.83/ 0.785 |
Compare with other methods
Requirement
Python 2.7
Pytorch 0.2.0
opencv-python
numpy
Train
python train.py --cuda
Evaluate
python test.py --cuda
Do Super resolution on your own images
python test.py --cuda --mode sr --testdir path_to_your_image
Reference