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SOTA
Image Super Resolution
Image Super Resolution On Bsd100 4X Upscaling
Image Super Resolution On Bsd100 4X Upscaling
평가 지표
PSNR
SSIM
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
PSNR
SSIM
Paper Title
Repository
HAT
28.05
0.7534
Activating More Pixels in Image Super-Resolution Transformer
BSRN
27.57
0.7353
Lightweight and Efficient Image Super-Resolution with Block State-based Recursive Network
ProSR
27.79
-
A Fully Progressive Approach to Single-Image Super-Resolution
DRCT-L
28.16
0.7577
DRCT: Saving Image Super-resolution away from Information Bottleneck
SPSR
25.505
0.6576
Structure-Preserving Super Resolution with Gradient Guidance
ZSSR
27.12
0.7211
"Zero-Shot" Super-Resolution using Deep Internal Learning
SRGAN
25.16
0.6688
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
CSNLN
27.8
0.7439
Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining
Manifold Simplification
27.66
0.7380
Beyond Deep Residual Learning for Image Restoration: Persistent Homology-Guided Manifold Simplification
SRResNet
27.58
0.762
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
DRCT
28.06
0.7533
DRCT: Saving Image Super-resolution away from Information Bottleneck
NLRN
27.48
0.7306
Non-Local Recurrent Network for Image Restoration
IMDN
27.56
-
Lightweight Image Super-Resolution with Information Multi-distillation Network
Config (e)
-
-
One-to-many Approach for Improving Super-Resolution
RDN
27.72
0.7419
Residual Dense Network for Image Super-Resolution
CPAT+
28.06
0.7532
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution
-
RFN
27.83
-
Progressive Perception-Oriented Network for Single Image Super-Resolution
GMFN
27.74
0.7421
Gated Multiple Feedback Network for Image Super-Resolution
WaveMixSR-V2
27.87
0.764
WaveMixSR-V2: Enhancing Super-resolution with Higher Efficiency
RL-CSC
27.44
0.7302
Image Super-Resolution via RL-CSC: When Residual Learning Meets Convolutional Sparse Coding
-
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