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Image Super Resolution
Image Super Resolution On Manga109 3X
Image Super Resolution On Manga109 3X
Metrics
PSNR
SSIM
Results
Performance results of various models on this benchmark
Columns
Model Name
PSNR
SSIM
Paper Title
Repository
DRLN+
34.94
0.9518
Densely Residual Laplacian Super-Resolution
CPAT
35.66
0.9559
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution
-
ML-CrAIST-Li
34.26
0.9492
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer
CSNLN
34.45
0.9502
Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining
HAT
35.84
0.9567
Activating More Pixels in Image Super-Resolution Transformer
CPAT+
35.77
0.9563
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution
-
HAT_FIR
35.92
-
SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolution
ML-CrAIST
34.42
0.9501
ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer
HAT-L
36.02
0.9576
Activating More Pixels in Image Super-Resolution Transformer
HAN+
34.87
0.9509
Single Image Super-Resolution via a Holistic Attention Network
HMA†
36.10
0.9580
HMANet: Hybrid Multi-Axis Aggregation Network for Image Super-Resolution
PMRN+
34.1
0.9480
Sequential Hierarchical Learning with Distribution Transformation for Image Super-Resolution
-
Hi-IR-L
36.12
0.9588
Hierarchical Information Flow for Generalized Efficient Image Restoration
-
SwinFIR
35.77
0.9563
SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolution
IMDN
33.61
-
Lightweight Image Super-Resolution with Information Multi-distillation Network
SRFBN
34.18
-
Feedback Network for Image Super-Resolution
LFFN-S
32.8
0.9381
Lightweight Feature Fusion Network for Single Image Super-Resolution
0 of 17 row(s) selected.
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