JingyunLiang / MANet

Official PyTorch code for Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution (MANet, ICCV2021)

https://arxiv.org/abs/2108.05302

JingyunLiang/MANet Issues

How to get the result of Table 4 in your paper?
Updated 4 months ago
A letter from afar
Updated 5 months ago
Issue about sv mode
Updated 6 months ago6
New Super-Resolution Benchmarks
Updated 7 months ago
About LR_Image PSNR/SSIM
Updated 7 months ago
shifted_l
Closed 7 months ago2
Questions about the paper
Updated 10 months ago
hello
Updated a year ago
Issue about class BatchBlur_SV in utils.util
Updated a year ago
hello
Updated a year ago10
CUDA out of memory
Updated a year ago3
Question about the prepare_testset
Updated a year ago5
some question about calculating psnr_kernel_y in stage1
Updated a year ago1
Training and OOM
Closed a year ago9
My val_psnr and test_psnr are different
Closed a year ago1
torch 1.9 there is some bugs in "run test.py"
Closed a year ago2
The method of creating kernels
Closed a year ago3
Looking forward to opening source!
Closed 2 years ago2
[How to get SR image by spatially variant estimated blur kernels]
Closed 2 years ago7
[Can estimated kernels(spatially variant) be used to deconvolution debluring?]
Closed 2 years ago2
[import error]
Closed 2 years ago2