| WaveMixSR-V2: Enhancing Super-resolution with Higher Efficiency | ✓ Link | 33.12 | 0.9326 | WaveMixSR-V2 | 2024-09-16 |
| WaveMixSR: A Resource-efficient Neural Network for Image Super-resolution | ✓ Link | 33.08 | 0.9322 | WaveMixSR | 2023-07-01 |
| DRCT: Saving Image Super-resolution away from Information Bottleneck | ✓ Link | 32.90 | 0.9078 | DRCT-L | 2024-03-31 |
| HMANet: Hybrid Multi-Axis Aggregation Network for Image Super-Resolution | ✓ Link | 32.79 | 0.9071 | HMA† | 2024-05-08 |
| Hierarchical Information Flow for Generalized Efficient Image Restoration | | 32.77 | 0.9092 | Hi-IR-L | 2024-11-27 |
| DRCT: Saving Image Super-resolution away from Information Bottleneck | ✓ Link | 32.75 | 0.9071 | DRCT | 2024-03-31 |
| Activating More Pixels in Image Super-Resolution Transformer | ✓ Link | 32.74 | 0.9066 | HAT-L | 2022-05-09 |
| SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolution | ✓ Link | 32.71 | | HAT_FIR | 2022-08-24 |
| Activating More Pixels in Image Super-Resolution Transformer | ✓ Link | 32.69 | 0.9060 | HAT | 2022-05-09 |
| Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution | | 32.66 | 0.9058 | CPAT+ | 2024-07-23 |
| Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution | | 32.64 | 0.9056 | CPAT | 2024-07-23 |
| SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolution | ✓ Link | 32.64 | 0.9054 | SwinFIR | 2022-08-24 |
| Pre-Trained Image Processing Transformer | ✓ Link | 32.48 | | IPT | 2020-12-01 |
| Densely Residual Laplacian Super-Resolution | ✓ Link | 32.47 | 0.9032 | DRLN+ | 2019-06-28 |
| Single Image Super-Resolution via a Holistic Attention Network | ✓ Link | 32.45 | 0.8431 | HAN+ | 2020-08-20 |
| Local Texture Estimator for Implicit Representation Function | ✓ Link | 32.44 | | LTE | 2021-11-17 |
| Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining | ✓ Link | 32.4 | 0.9024 | CSNLN | 2020-06-02 |
| Resolution Enhancement Processing on Low Quality Images Using Swin Transformer Based on Interval Dense Connection Strategy | ✓ Link | 32.34 | 0.9022 | SwinOIR | 2023-03-16 |
| Hierarchical Back Projection Network for Image Super-Resolution | ✓ Link | 32.33 | 0.902 | HBPN | 2019-06-17 |
| Feedback Network for Image Super-Resolution | ✓ Link | 32.29 | | SRFBN | 2019-03-23 |
| Multi-level Wavelet-CNN for Image Restoration | ✓ Link | 32.23 | | MWCNN | 2018-05-18 |
| Lightweight Image Super-Resolution with Information Multi-distillation Network | ✓ Link | 32.19 | | IMDN | 2019-09-26 |
| Fast, Accurate and Lightweight Super-Resolution with Neural Architecture Search | ✓ Link | 32.12 | | FALSR-A | 2019-01-22 |
| Fast, Accurate, and Lightweight Super-Resolution with Cascading Residual Network | ✓ Link | 32.09 | | CARN [[Ahn et al.2018]] | 2018-03-23 |
| Image Restoration Using Convolutional Auto-encoders with Symmetric Skip Connections | ✓ Link | 31.99 | 0.8974 | RED30 | 2016-06-29 |
| Lightweight Feature Fusion Network for Single Image Super-Resolution | ✓ Link | 31.96 | | LFFN-S | 2019-02-15 |
| Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising | ✓ Link | 31.9 | | DnCNN-3 | 2016-08-13 |
| Image Restoration Using Deep Regulated Convolutional Networks | ✓ Link | 31.86 | | RC-Net | 2019-10-19 |
| Deeply-Recursive Convolutional Network for Image Super-Resolution | ✓ Link | 31.85 | | DRCN [[Kim et al.2016b]] | 2015-11-14 |
| Accelerating the Super-Resolution Convolutional Neural Network | ✓ Link | 31.53 | | FSRCNN [[Dong et al.2016]] | 2016-08-01 |