PSNR: 30.92SSIM: 0.8981
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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
PSNR: 30.63SSIM: 0.8934
PSNR: 31.07SSIM: 0.902
PSNR: 31.00SSIM: 0.8984
PSNR: 28.89SSIM: 0.8676
PSNR: 30.77
PSNR: 27.15
SSIM: 0.795
PSNR: 29.37SSIM: 0.8746
PSNR: 28.16SSIM: 0.7577
PSNR: 23.14SSIM: 0.6577
PSNR: 28.818
PSNR: 28.73
PSNR: 29.13SSIM: 0.8712
PSNR: 27.24
PSNR: 28.17
PSNR: 29.41
PSNR: 28.13
LPIPS: 0.1007
PSNR: 29.49
SSIM: 0.8169
PSNR: 28.87SSIM: 0.8674
PSNR: 29.21SSIM: 0.8710