PSNR: 31.47SSIM: 0.8584
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Image Super-Resolution
Image Super-Resolution is a machine learning task where the goal is to increase the resolution of an image, often by a factor of 4x or more, while maintaining its content and details as much as possible. The end result is a high-resolution version of the original image. This task can be used for various applications such as improving image quality, enhancing visual detail, and increasing the accuracy of computer vision algorithms.
논문
#params (K): 1268FLOPs(G): 84.1
PSNR: 31.37
PSNR: 31.53
PSNR: 23.65
PSNR: 31.9
PSNR: 31.19SSIM: 0.8559
PSNR: 23.10
PSNR: 31.85
PSNR: 27.11
PSNR: 27.29SSIM: 0.811
PSNR: 32.12
PSNR: 32.09
PSNR: 20.24
PSNR: 31.55SSIM: 0.8616
PSNR: 31.47SSIM: 0.8585
PSNR: 31.99SSIM: 0.8974
PSNR: 31.86
PSNR: 26.24
PSNR: 26.26
PSNR: 27.21
PSNR: 31.96
PSNR: 32.19
PSNR: 32.23
PSNR: 24.49
Frechet Inception Distance: 11.72
PSNR: 21.63