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SOTA
이미지 초해상화
Image Super Resolution On Set14 4X Upscaling
Image Super Resolution On Set14 4X Upscaling
평가 지표
PSNR
SSIM
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
PSNR
SSIM
Paper Title
Repository
ATD
29.24
0.7974
Transcending the Limit of Local Window: Advanced Super-Resolution Transformer with Adaptive Token Dictionary
Manifold Simplification
28.80
0.7856
Beyond Deep Residual Learning for Image Restoration: Persistent Homology-Guided Manifold Simplification
BSRN
28.56
0.7803
Lightweight and Efficient Image Super-Resolution with Block State-based Recursive Network
HBPN
28.67
0.785
Hierarchical Back Projection Network for Image Super-Resolution
Extracter-rec
28.09
0.782
EXTRACTER: Efficient Texture Matching with Attention and Gradient Enhancing for Large Scale Image Super Resolution
HMA†
29.51
0.8019
HMANet: Hybrid Multi-Axis Aggregation Network for Image Super-Resolution
ENet-E
28.42
0.7774
EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis
SPSR
26.64
0.7930
Structure-Preserving Super Resolution with Gradient Guidance
MaIR
29.2
0.7958
MaIR: A Locality- and Continuity-Preserving Mamba for Image Restoration
-
ProSR
28.94
-
A Fully Progressive Approach to Single-Image Super-Resolution
CRAFT
28.85
0.7872
Exploring Frequency-Inspired Optimization in Transformer for Efficient Single Image Super-Resolution
SESR
28.32
0.784
SESR: Single Image Super Resolution with Recursive Squeeze and Excitation Networks
AESOP
27.421
0.7438
Auto-Encoded Supervision for Perceptual Image Super-Resolution
GMFN
28.84
0.7888
Gated Multiple Feedback Network for Image Super-Resolution
CPAT
29.34
0.7991
Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution
-
bicubic
-
0.7486
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
SPMC
27.57
0.76
Detail-revealing Deep Video Super-resolution
4PP-EUSR
27.6222
0.7419
Deep Learning-based Image Super-Resolution Considering Quantitative and Perceptual Quality
Edge-informed SR
25.19
0.894
Edge-Informed Single Image Super-Resolution
S-RFN
-
0.7946
Progressive Perception-Oriented Network for Single Image Super-Resolution
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