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SotA/Computer Code/Blind Image Deblurring

Blind Image Deblurring

37 benchmarks0 papers

Blind Image Deblurring is a classical problem in image processing and computer vision, which aims to recover a latent image from a blurred input.

<span class="description-source">Source: Learning a Discriminative Prior for Blind Image Deblurring </span>

Benchmarks

Blind Image Deblurring on GoPro

Blind Image Deblurring on HIDE (trained on GOPRO)

PSNR (sRGB)SSIM (sRGB)Params (M)

Blind Image Deblurring on RealBlur-R (trained on GoPro)

SSIM (sRGB)PSNR (sRGB)

Blind Image Deblurring on RealBlur-J

PSNR (sRGB)SSIM (sRGB)Params(M)

Blind Image Deblurring on RealBlur-R

PSNR (sRGB)SSIM (sRGB)Params

Blind Image Deblurring on RealBlur-J (trained on GoPro)

PSNR (sRGB)SSIM (sRGB)

Blind Image Deblurring on RSBlur

Average PSNR SSIM

Blind Image Deblurring on MSU BASED

Subjective SSIM VMAF LPIPS PSNR ERQAv2.0

Blind Image Deblurring on DVD

Blind Image Deblurring on Beam-Splitter Deblurring (BSD)

Blind Image Deblurring on BASED

PSNR VMAF ERQAv2.0 LPIPS SSIM

Blind Image Deblurring on DVD

Blind Image Deblurring on REDS

Blind Image Deblurring on RSBlur (trained on synthetic)

Blind Image Deblurring on .

10 Images, 4*4 Stitching, Exact Accuracy

Blind Image Deblurring on HIDE

Blind Image Deblurring on Second dialogue state tracking challenge