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SOTA
Image Super Resolution
Image Super Resolution On Urban100 2X
Image Super Resolution On Urban100 2X
评估指标
PSNR
SSIM
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
PSNR
SSIM
Paper Title
Repository
SwinOIR
32.83
0.9353
Resolution Enhancement Processing on Low Quality Images Using Swin Transformer Based on Interval Dense Connection Strategy
HMA†
35.24
0.9513
HMANet: Hybrid Multi-Axis Aggregation Network for Image Super-Resolution
SPBP-L+
32.07
0.9277
Sub-Pixel Back-Projection Network For Lightweight Single Image Super-Resolution
FACD
32.878
-
Feature-domain Adaptive Contrastive Distillation for Efficient Single Image Super-Resolution
-
CSNLN
33.25
0.9386
Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining
MWCNN
32.3
-
Multi-level Wavelet-CNN for Image Restoration
VDSR [[Kim et al.2016a]]
30.76
-
Accurate Image Super-Resolution Using Very Deep Convolutional Networks
HAT
34.81
0.9489
Activating More Pixels in Image Super-Resolution Transformer
DRCT-L
35.17
0.9516
DRCT: Saving Image Super-resolution away from Information Bottleneck
DBPN-RES-MR64-3
32.92
0.935
Deep Back-Projection Networks for Single Image Super-resolution
PMRN+
32.78
0.9342
Sequential Hierarchical Learning with Distribution Transformation for Image Super-Resolution
-
DRLN+
33.54
0.9402
Densely Residual Laplacian Super-Resolution
HAT-L
35.09
0.9505
Activating More Pixels in Image Super-Resolution Transformer
ML-CrAIST-Li
32.93
0.9361
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer
DRCN [[Kim et al.2016b]]
30.75
-
Deeply-Recursive Convolutional Network for Image Super-Resolution
DnCNN-3
30.74
-
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
SwinFIR
34.57
0.9473
SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolution
Hi-IR-L
35.16
0.9505
Hierarchical Information Flow for Generalized Efficient Image Restoration
-
ML-CrAIST
33.04
0.937
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer
DRCT
34.54
0.9474
DRCT: Saving Image Super-resolution away from Information Bottleneck
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