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홈
SOTA
Image Denoising
Image Denoising On Sidd
Image Denoising On Sidd
평가 지표
PSNR (sRGB)
SSIM (sRGB)
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
PSNR (sRGB)
SSIM (sRGB)
Paper Title
Repository
AKDT
39.70
0.961
AKDT: Adaptive Kernel Dilation Transformer for Effective Image Denoising
MIRNet
39.72
0.959
Learning Enriched Features for Real Image Restoration and Enhancement
MAXIM-3S
39.96
0.960
MAXIM: Multi-Axis MLP for Image Processing
HINet
39.99
0.958
HINet: Half Instance Normalization Network for Image Restoration
VDN
39.28
0.956
Variational Denoising Network: Toward Blind Noise Modeling and Removal
RIDNet
38.71
0.951
Real Image Denoising with Feature Attention
DRANet
-
0.957
Dual Residual Attention Network for Image Denoising
NAFNet
40.30
0.961
Simple Baselines for Image Restoration
DANet+
39.47
0.957
Dual Adversarial Network: Toward Real-world Noise Removal and Noise Generation
SSAMAN
40.08
0.962
Single Stage Adaptive Multi-Attention Network for Image Restoration
CGNet
40.39
0.964
CascadedGaze: Efficiency in Global Context Extraction for Image Restoration
AINDNet
38.95
0.952
Transfer Learning from Synthetic to Real-Noise Denoising with Adaptive Instance Normalization
NBNet
-
0.973
NBNet: Noise Basis Learning for Image Denoising with Subspace Projection
Restormer
40.02
0.960
Restormer: Efficient Transformer for High-Resolution Image Restoration
CBDNet
30.78
0.801
Toward Convolutional Blind Denoising of Real Photographs
SADNet
39.46
0.957
Spatial-Adaptive Network for Single Image Denoising
SRMNet
39.72
0.959
Selective Residual M-Net for Real Image Denoising
KBNet
40.35
0.972
KBNet: Kernel Basis Network for Image Restoration
CycleISP
39.52
0.957
CycleISP: Real Image Restoration via Improved Data Synthesis
Uformer-B
39.89
0.960
Uformer: A General U-Shaped Transformer for Image Restoration
0 of 22 row(s) selected.
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