Image Super Resolution On Div2K Val 4X

LPIPS

PSNR

SSIM

평가 결과

이 벤치마크에서 각 모델의 성능 결과

비교 표

모델 이름	LPIPS	PSNR	SSIM
local-implicit-normalizing-flow-for-arbitrary	0.112	27.33	0.76
enhanced-deep-residual-networks-for-single	-	29.25	0.9017
implicit-diffusion-models-for-continuous	-	26.55	0.75
image-restoration-through-generalized	0.220	26.89	0.7478
flexible-style-image-super-resolution-using	0.1028	27.51	0.789
implicit-diffusion-models-for-continuous	-	27.03	0.77
implicit-diffusion-models-for-continuous	-	26.7	0.77
local-implicit-normalizing-flow-for-arbitrary	0.248	29.14	0.83
implicit-diffusion-models-for-continuous	-	27.02	0.76
learning-continuous-image-representation-with	-	29	0.89
implicit-diffusion-models-for-continuous	-	26.61	0.74
boosting-flow-based-generative-super	0.109	27.51	0.78
implicit-diffusion-models-for-continuous	-	26.22	0.75
multi-step-reinforcement-learning-for-single	-	28.08	0.8140
boosting-flow-based-generative-super	0.105	28.00	0.78
auto-encoded-supervision-for-perceptual-image	0.0893	29.137	0.8023
residual-conditioned-optimal-transport	0.104	28.41	0.804
srflow-learning-the-super-resolution-space	0.12	27.09	0.76
implicit-diffusion-models-for-continuous	-	27.59	0.78
flexible-style-image-super-resolution-using	0.239	29.24	0.8383
perception-oriented-single-image-super	0.0957	27.69	0.7932