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ホーム
SOTA
画像超解像度
Image Super Resolution On Manga109 4X
Image Super Resolution On Manga109 4X
評価指標
PSNR
SSIM
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
Columns
モデル名
PSNR
SSIM
Paper Title
Repository
HMA†
33.19
0.9344
HMANet: Hybrid Multi-Axis Aggregation Network for Image Super-Resolution
DRCT-L
33.14
0.9347
DRCT: Saving Image Super-resolution away from Information Bottleneck
Hi-IR-L
33.13
0.9366
Hierarchical Information Flow for Generalized Efficient Image Restoration
-
HAT-L
33.09
0.9335
Activating More Pixels in Image Super-Resolution Transformer
HAT_FIR
33.03
-
SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolution
DRCT
32.96
0.9324
DRCT: Saving Image Super-resolution away from Information Bottleneck
HAT
32.87
0.9319
Activating More Pixels in Image Super-Resolution Transformer
CPAT+
32.85
0.9318
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution
-
SwinFIR
32.83
0.9314
SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolution
RGT+
32.68
0.9303
Recursive Generalization Transformer for Image Super-Resolution
DAT+
32.67
0.9301
Dual Aggregation Transformer for Image Super-Resolution
MaIR+
32.66
0.9297
MaIR: A Locality- and Continuity-Preserving Mamba for Image Restoration
DAT
32.51
0.9291
Dual Aggregation Transformer for Image Super-Resolution
RGT
32.50
0.9291
Recursive Generalization Transformer for Image Super-Resolution
MaIR
32.46
0.9284
MaIR: A Locality- and Continuity-Preserving Mamba for Image Restoration
SwinIR
32.22
0.9273
SwinIR: Image Restoration Using Swin Transformer
ABPN
31.79
0.921
Image Super-Resolution via Attention based Back Projection Networks
DRLN+
31.78
0.9211
Densely Residual Laplacian Super-Resolution
+SPN
31.75
0.9229
Learning from History: Task-agnostic Model Contrastive Learning for Image Restoration
DBPN-RES-MR64-3
31.74
0.921
Deep Back-Projection Networks for Single Image Super-resolution
0 of 49 row(s) selected.
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