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Super-Resolution on Set14

33.02PSNRVDSR
21.881624.773327.66530.5567Aug 1, 2016Jan 23, 2018Jul 17, 2019Jan 7, 2021Jul 1, 2022Dec 23, 2023Jun 15, 2025

Evaluation results

MethodLinks
VDSRScale=2, Kernel=Bicubic, Channel=Y2017.0433.02————————
Proposed_LScale=2, Kernel=Bicubic, Channel=Y2017.0432.88————————
SRBM3DScale=2, Kernel=Bicubic, Channel=Y2017.0432.8————————
Proposed_CScale=2, Kernel=Bicubic, Channel=Y2017.0432.79————————
FSRCNNupscaling factor=2, training dataset=91-image and General-1002016.0832.63————————
SCNupscaling factor=22016.0832.56————————
SRFupscaling factor=22016.0832.52————————
SRCNN-Exupscaling factor=22016.0832.45————————
SRCNNScale=2, Kernel=Bicubic, Channel=Y2017.0432.43————————
A+upscaling factor=22016.0832.28————————
FSRCNN-supscaling factor=2, training dataset=91-image and General-1002016.0832.28————————
SRBM3DCScale=2, Kernel=Bicubic, Channel=Y2017.0432.25————————
SRCNNupscaling factor=22016.0832.18————————
KKupscaling factor=22016.0832.11————————
SRBM3DGScale=2, Kernel=Bicubic, Channel=Y2017.0432.09————————
SPMSRScale=2, Kernel=Bicubic, Channel=Y2017.0431.96————————
VDSRScale=2, Kernel=Bicubic, Channel=RGB2017.0430.9————————
Proposed_LScale=2, Kernel=Bicubic, Channel=RGB2017.0430.79————————
Proposed_CScale=2, Kernel=Bicubic, Channel=RGB2017.0430.78————————
SRCNNScale=2, Kernel=Bicubic, Channel=RGB2017.0430.43————————
SRBM3DCScale=2, Kernel=Bicubic, Channel=RGB2017.0430.32————————
Bicubicupscaling factor=22016.0830.23————————
SRBM3DGScale=2, Kernel=Bicubic, Channel=RGB2017.0430.15————————
SPMSRScale=2, Kernel=Bicubic, Channel=RGB2017.0430.05————————
VDSRScale=3, Kernel=Bicubic, Channel=Y2017.0429.77————————
Proposed_LScale=3, Kernel=Gaussian, Channel=Y2017.0429.63————————
Proposed_LScale=3, Kernel=Bicubic, Channel=Y2017.0429.61————————
SRBM3DScale=3, Kernel=Bicubic, Channel=Y2017.0429.6————————
Proposed_CScale=3, Kernel=Gaussian, Channel=Y2017.0429.55————————
Proposed_CScale=3, Kernel=Bicubic, Channel=Y2017.0429.5————————
FSRCNNupscaling factor=3, training dataset=91-image and General-1002016.0829.43————————
SCNupscaling factor=32016.0829.41————————
SRBM3DCScale=3, Kernel=Gaussian, Channel=Y2017.0429.39————————
SRCNN-Exupscaling factor=32016.0829.3————————
SRCNNScale=3, Kernel=Bicubic, Channel=Y2017.0429.27————————
SRBM3DCScale=3, Kernel=Bicubic, Channel=Y2017.0429.27————————
NCSRScale=3, Kernel=Gaussian, Channel=Y2017.0429.26————————
SRFupscaling factor=32016.0829.23————————
SRBM3DGScale=3, Kernel=Gaussian, Channel=Y2017.0429.18————————
A+upscaling factor=32016.0829.13————————
FSRCNN-supscaling factor=3, training dataset=91-image and General-1002016.0829.13————————
SRBM3DGScale=3, Kernel=Bicubic, Channel=Y2017.0429.11————————
SRCNNupscaling factor=32016.0829————————
KKupscaling factor=32016.0828.94————————
SPMSRScale=3, Kernel=Bicubic, Channel=Y2017.0428.93————————
SPMSRScale=3, Kernel=Gaussian, Channel=Y2017.0428.89————————
VDSRScale=3, Kernel=Bicubic, Channel=RGB2017.0427.85————————
VDSRScale=3, Kernel=Gaussian, Channel=Y2017.0427.8————————
Proposed_LScale=3, Kernel=Bicubic, Channel=RGB2017.0427.72————————
SRCNNScale=3, Kernel=Gaussian, Channel=Y2017.0427.71————————
Proposed_CScale=3, Kernel=Gaussian, Channel=RGB2017.0427.7————————
Proposed_CScale=3, Kernel=Bicubic, Channel=RGB2017.0427.67————————
SCNupscaling factor=42016.0827.64————————
SRBM3DCScale=3, Kernel=Gaussian, Channel=RGB2017.0427.6————————
FSRCNNupscaling factor=4, training dataset=91-image and General-1002016.0827.59————————
Proposed_LScale=3, Kernel=Gaussian, Channel=RGB2017.0427.59————————
Bicubicupscaling factor=32016.0827.54————————
SRCNN-Exupscaling factor=42016.0827.5————————
SRBM3DCScale=3, Kernel=Bicubic, Channel=RGB2017.0427.47————————
SRCNNScale=3, Kernel=Bicubic, Channel=RGB2017.0427.44————————
SRFupscaling factor=42016.0827.41————————
A+upscaling factor=42016.0827.32————————
SRBM3DGScale=3, Kernel=Bicubic, Channel=RGB2017.0427.32————————
SRBM3DGScale=3, Kernel=Gaussian, Channel=RGB2017.0427.24————————
SRCNNupscaling factor=42016.0827.2————————
FSRCNN-supscaling factor=4, training dataset=91-image and General-1002016.0827.19————————
SPMSRScale=3, Kernel=Bicubic, Channel=RGB2017.0427.17————————
KKupscaling factor=42016.0827.14————————
SPMSRScale=3, Kernel=Gaussian, Channel=RGB2017.0427.01————————
NCSRScale=3, Kernel=Gaussian, Channel=RGB2017.0426.98————————
VDSRScale=3, Kernel=Gaussian, Channel=RGB2017.0426.11————————
SRCNNScale=3, Kernel=Gaussian, Channel=RGB2017.0426.02————————
Bicubicupscaling factor=42016.0826————————
Implicit Adaptive DropoutBackbone=RRDB2025.0622.61————————
Explicit Adaptive DropoutBackbone=RRDB2025.0622.56————————
Simple-AlignBackbone=RRDB2025.0622.51————————
Explicit Adaptive DropoutBackbone=SRResNet2025.0622.34————————
Implicit Adaptive DropoutBackbone=SRResNet2025.0622.32————————
Simple-AlignBackbone=SRResNet2025.0622.31————————
DropoutBackbone=SRResNet, Scale=x42025.06—23.1122.9220.6122.1621.8722.0121.6421.86
DropoutBackbone=SwinIR, Scale=x42025.06—23.823.3621.5923.0922.422.2421.8422.17
Explicit Adaptive DropoutBackbone=SRResNet, Scale=x42025.06—23.4223.221.1422.4622.1522.2921.8422.09
Explicit Adaptive DropoutBackbone=SwinIR, Scale=x42025.06—23.9223.5621.6723.2922.9122.4122.1922.3
Implicit Adaptive DropoutBackbone=SRResNet, Scale=x42025.06—23.4723.2121.1522.5122.1222.2921.8422.13
Implicit Adaptive DropoutBackbone=SwinIR, Scale=x42025.06—23.9523.4121.6923.1922.7822.3622.1922.23
SRResNetRegularization=None, Scale=x42025.06—22.622.520.8121.8421.8121.721.4421.59
SwinIRRegularization=None, Scale=x42025.06—23.7623.4721.5623.0422.222.2621.8222.11