Tasks SotA Datasets Papers Methods Submit About

Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable Benchmarks All SotA Datasets Papers Methods

Community

Submit Results About

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Models/MIMO-UNet++

MIMO-UNet++

Reported on 30 benchmarks across 7 tasks · 1 paper · 4 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Audio11 results

10-shot image generationonRealBlur-J
PSNR (sRGB)· uses extra data· 2021-08-11
32.05
best: 33.96 (AdaRevD)
SOTA
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
10-shot image generationonRealBlur-J
Params(M)· uses extra data· 2021-08-11
16.1
best: 22.2 (MAXIM)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
10-shot image generationonRealBlur-J
SSIM (sRGB)· uses extra data· 2021-08-11
0.921
best: 0.946 (ALGNet)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
10-shot image generationonGoPro
PSNR· 2021-08-11
32.68
best: 35.98 (BSSTNet)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
10-shot image generationonGoPro
SSIM· 2021-08-11
0.959
best: 0.9792 (BSSTNet)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
10-shot image generationonGoPro
PSNR· 2021-08-11
32.68
best: 35.98 (BSSTNet)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
10-shot image generationonGoPro
Params (M)· 2021-08-11
16.1
best: 80.3 (UFPDeblur)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
10-shot image generationonGoPro
SSIM· 2021-08-11
0.959
best: 0.9792 (BSSTNet)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
1 Image, 2*2 StitchionGoPro
PSNR· 2021-08-11
32.68
best: 34.6 (AdaRevD)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
1 Image, 2*2 StitchionGoPro
Params (M)· 2021-08-11
16.1
best: 80.3 (UFPDeblur)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
1 Image, 2*2 StitchionGoPro
SSIM· 2021-08-11
0.959
best: 0.972 (AdaRevD)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054

Computer Vision8 results

DeblurringonRealBlur-J
PSNR (sRGB)· uses extra data· 2021-08-11
32.05
best: 33.96 (AdaRevD)
SOTA
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
DeblurringonRealBlur-J
Params(M)· uses extra data· 2021-08-11
16.1
best: 22.2 (MAXIM)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
DeblurringonRealBlur-J
SSIM (sRGB)· uses extra data· 2021-08-11
0.921
best: 0.946 (ALGNet)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
DeblurringonGoPro
PSNR· 2021-08-11
32.68
best: 35.98 (BSSTNet)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
DeblurringonGoPro
SSIM· 2021-08-11
0.959
best: 0.9792 (BSSTNet)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
Image DeblurringonGoPro
PSNR· 2021-08-11
32.68
best: 34.6 (AdaRevD)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
Image DeblurringonGoPro
Params (M)· 2021-08-11
16.1
best: 80.3 (UFPDeblur)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
Image DeblurringonGoPro
SSIM· 2021-08-11
0.959
best: 0.972 (AdaRevD)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054

Methodology8 results

2D ClassificationonRealBlur-J
PSNR (sRGB)· uses extra data· 2021-08-11
32.05
best: 33.96 (AdaRevD)
SOTA
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
2D ClassificationonRealBlur-J
Params(M)· uses extra data· 2021-08-11
16.1
best: 22.2 (MAXIM)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
2D ClassificationonRealBlur-J
SSIM (sRGB)· uses extra data· 2021-08-11
0.921
best: 0.946 (ALGNet)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
2D ClassificationonGoPro
PSNR· 2021-08-11
32.68
best: 35.98 (BSSTNet)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
2D ClassificationonGoPro
SSIM· 2021-08-11
0.959
best: 0.9792 (BSSTNet)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
16konGoPro
PSNR· 2021-08-11
32.68
best: 34.6 (AdaRevD)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
16konGoPro
Params (M)· 2021-08-11
16.1
best: 80.3 (UFPDeblur)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
16konGoPro
SSIM· 2021-08-11
0.959
best: 0.972 (AdaRevD)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054

Computer Code5 results

Blind Image DeblurringonRealBlur-J
PSNR (sRGB)· uses extra data· 2021-08-11
32.05
best: 33.96 (AdaRevD)
SOTA
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
Blind Image DeblurringonRealBlur-J
Params(M)· uses extra data· 2021-08-11
16.1
best: 22.2 (MAXIM)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
Blind Image DeblurringonRealBlur-J
SSIM (sRGB)· uses extra data· 2021-08-11
0.921
best: 0.946 (ALGNet)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
Blind Image DeblurringonGoPro
PSNR· 2021-08-11
32.68
best: 35.98 (BSSTNet)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054
Blind Image DeblurringonGoPro
SSIM· 2021-08-11
0.959
best: 0.9792 (BSSTNet)
Rethinking Coarse-to-Fine Approach in Single Image Deblurring arXiv:2108.05054