Deep Learning for Image Super-Resolution: A Survey
Pre-upsampling
Post-upsampling
Progressive Upsampling
Iterative Up-and-down Sampling
Visible Images
Infrared Images
Models For Visible Images
Models For Infrared Images
Learning a Deep Convolutional Network for Image Super-Resolution(SRCNN)
Memnet: A persistent memory network for image restoration(MemNet)
Deeply-recursive convolutional network for image super-resolution(DRCN)
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network(SRGAN)
| Name | Amount | Format | Link |
|---|---|---|---|
| Set5 | 5 | PNG | Downoad |
| Set14 | 14 | PNG | Downoad |
| BSDS300 | 300 | JPG | Downoad |
| BSDS500 | 500 | JPG | Downoad |
| DIV2K(NTIRE2017) | 1000 | PNG | Website |
| Name | Amount | Resolution | Format | Link |
|---|---|---|---|---|
| CVC-09 | 13184 | 640*480 | PNG | Website |
| CVC-14 | 31962 | 640*471, 64*128 | TIF | Website |
| CVC-09-1K(Trainset For HetSRWGAN) | 1000 | 640*480 | PNG | Website |
| IR100(Trainset For PSRGAN) | 100 | 640*480 | PNG | Website |
| Method | Publication | Keywords(Framkworks, Upsampling Methods, Network Design, Learning Strategies) |
|---|---|---|
| SRResNet | 2017, CVPR | Post-upsampling, Sub-pixel, Residual |
| SRGAN | 2017, CVPR | |
| BSRGAN | 2021, ICCV | Blind SR, Complex Degradation Model, Random Shuffle |
| USRNet | 2020, SVPR | Integrating Model-based Method and Learning-based Method, Data Module + Prioe Module + Hyper-parameter Module |
| Method | Publication | Keywords(Framkworks, Upsampling Methods, Network Design, Learning Strategies) |
|---|