PSNR: 31.63SSIM: 0.945FID: 22.27
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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: 36.02SSIM: 0.9576
PSNR: 35.77SSIM: 0.9563
PSNR: 25.05SSIM: 0.607
PSNR: 34.94SSIM: 0.9518
PSNR: 34.42SSIM: 0.9501
PSNR: 34.87SSIM: 0.9509
PSNR: 35.92
LPIPS: 0.071DISTS: 0.0762PSNR: 30.401SSIM: 0.8328
PSNR: 24.30SSIM: 0.614
PSNR: 24.28
PSNR: 34.18
PSNR: 24.96SSIM: 0.642
PSNR: 25.08SSIM: 0.638
PSNR: 34.45SSIM: 0.9502
PSNR: 34.05
PSNR: 32.8SSIM: 0.9381
PSNR: 33.61
PSNR: 34.1SSIM: 0.9480