Image Super Resolution On Div2K Val 4X

Métriques

LPIPS

PSNR

SSIM

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	LPIPS	PSNR	SSIM	Paper Title	Repository
LINF	0.112	27.33	0.76	Local Implicit Normalizing Flow for Arbitrary-Scale Image Super-Resolution	-
EDSR	-	29.25	0.9017	Enhanced Deep Residual Networks for Single Image Super-Resolution	-
RankSRGAN	-	26.55	0.75	Implicit Diffusion Models for Continuous Super-Resolution	-
GOUB	0.220	26.89	0.7478	Image Restoration Through Generalized Ornstein-Uhlenbeck Bridge	-
FxSR-PD t=0.8	0.1028	27.51	0.789	Flexible Style Image Super-Resolution using Conditional Objective	-
LAR-SR	-	27.03	0.77	Implicit Diffusion Models for Continuous Super-Resolution	-
Bicubic	-	26.7	0.77	Implicit Diffusion Models for Continuous Super-Resolution	-
LINF t=0.0	0.248	29.14	0.83	Local Implicit Normalizing Flow for Arbitrary-Scale Image Super-Resolution	-
HCFlow	-	27.02	0.76	Implicit Diffusion Models for Continuous Super-Resolution	-
LIIF	-	29	0.89	Learning Continuous Image Representation with Local Implicit Image Function	-
HCFlow++	-	26.61	0.74	Implicit Diffusion Models for Continuous Super-Resolution	-
SRFlow-LP	0.109	27.51	0.78	Boosting Flow-based Generative Super-Resolution Models via Learned Prior	-
ESRGAN	-	26.22	0.75	Implicit Diffusion Models for Continuous Super-Resolution	-
PixelRL-SR	-	28.08	0.8140	Multi-Step Reinforcement Learning for Single Image Super-Resolution
LINF-LP	0.105	28.00	0.78	Boosting Flow-based Generative Super-Resolution Models via Learned Prior	-
AESOP	0.0893	29.137	0.8023	Auto-Encoded Supervision for Perceptual Image Super-Resolution	-
RCOT	0.104	28.41	0.804	Residual-Conditioned Optimal Transport: Towards Structure-Preserving Unpaired and Paired Image Restoration	-
SRFlow	0.12	27.09	0.76	SRFlow: Learning the Super-Resolution Space with Normalizing Flow	-
IDM	-	27.59	0.78	Implicit Diffusion Models for Continuous Super-Resolution	-
FxSR-PD t=0.0	0.239	29.24	0.8383	Flexible Style Image Super-Resolution using Conditional Objective	-

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