Low-Light Image Enhancement on LOL-Real (test)
25.61PSNRPTG-RM (SNR backbone)
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| PTG-RM (SNR backbone)Prior=BLIP2, Backbone=SNR2024.03 | 25.61 | 0.891 | |
| Unsupervised Night Image Enhancement NetworkLearning=UL2022.07 | 25.51 | 0.8 | |
| PTG-RM (SNR backbone)Prior=CLIP, Backbone=SNR2024.03 | 25.5 | 0.892 | |
| PTG-RM (SNR backbone)Prior=Restoration models (SDSD), Backbone=SNR2024.03 | 25.24 | 0.887 | |
| PTG-RM (SNR backbone)Prior=Stable Diffusion, Backbone=SNR2024.03 | 25.19 | 0.874 | |
| PTG-RM (SNR backbone)Mode=Feature Refinement, Backbone=SNR2024.03 | 24.9 | 0.888 | |
| PTG-RM (URetinex backbone)Prior=CLIP, Backbone=URetinex2024.03 | 24.7 | 0.878 | |
| PTG-RM (URetinex backbone)Mode=Feature Refinement, Backbone=URetinex2024.03 | 24.56 | 0.87 | |
| PTG-RM (URetinex backbone)Prior=Stable Diffusion, Backbone=URetinex2024.03 | 23.99 | 0.866 | |
| PTG-RM (URetinex backbone)Prior=Restoration models (SDSD), Backbone=URetinex2024.03 | 23.99 | 0.862 | |
| PTG-RM (URetinex backbone)Prior=BLIP2, Backbone=URetinex2024.03 | 23.57 | 0.869 | |
| PTG-RM (UHD backbone)Prior=CLIP, Backbone=UHD2024.03 | 22.91 | 0.767 | |
| PTG-RM (UHD backbone)Mode=Feature Refinement, Backbone=UHD2024.03 | 22.74 | 0.764 | |
| PTG-RM (UHD backbone)Prior=Stable Diffusion, Backbone=UHD2024.03 | 22.35 | 0.758 | |
| PTG-RM (UHD backbone)Prior=BLIP2, Backbone=UHD2024.03 | 21.83 | 0.732 | |
| PTG-RM (UHD backbone)Prior=Restoration models (SDSD), Backbone=UHD2024.03 | 21.71 | 0.737 | |
| SCI + Ours-cRefinement Module=Ours-c, Pre-trained Model=CLIP2024.03 | 21.62 | 0.781 | |
| SNRRefinement=None2024.03 | 21.48 | 0.849 | |
| URetinexRefinement=None2024.03 | 21.16 | 0.84 | |
| ZDLearning=ZSL2022.07 | 20.54 | 0.78 | |
| SCIRefinement Module=None2024.03 | 20.28 | 0.752 | |
| UHDRefinement=None2024.03 | 19.87 | 0.706 | |
| DRBNLearning=SSL2022.07 | 19.66 | 0.76 | |
| RUAS + Ours-cRefinement Module=Ours-c, Pre-trained Model=CLIP2024.03 | 19.53 | 0.747 | |
| SICELearning=SL2022.07 | 19.4 | 0.69 | |
| ZeroDCE + Ours-cRefinement Module=Ours-c, Pre-trained Model=CLIP2024.03 | 18.79 | 0.614 | |
| RUASRefinement Module=None2024.03 | 18.37 | 0.723 | |
| SharmaLearning=SSL2022.07 | 18.34 | 0.64 | |
| EGLearning=UL2022.07 | 18.23 | 0.61 | |
| ZeroDCERefinement Module=None2024.03 | 18.06 | 0.58 | |
| LLNetLearning=SL2022.07 | 17.56 | 0.54 | |
| RRMLearning=Opti2022.07 | 17.34 | 0.68 | |
| SRIELearning=Opti2022.07 | 17.34 | 0.68 | |
| JEDLearning=Opti2022.07 | 17.33 | 0.66 | |
| AfifiLearning=SL2022.07 | 16.38 | 0.53 | |
| RNLearning=SL2022.07 | 15.47 | 0.56 | |
| RUASLearning=SL2022.07 | 15.33 | 0.52 | |
| RRDNetLearning=ZSL2022.07 | 14.85 | 0.56 | |
| DUPELearning=SL2022.07 | 13.27 | 0.45 | |
| MIRNetLearning=ZSL2022.07 | 12.67 | 0.41 | |
| RDIPLearning=ZSL2022.07 | 11.43 | 0.36 | |
| InputLearning=NA2022.07 | 9.72 | 0.18 |