Image Super Resolution On Div2K Val 4X
评估指标
LPIPS
PSNR
SSIM
评测结果
各个模型在此基准测试上的表现结果
比较表格
模型名称 | 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 |