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Models/FSRCNN

FSRCNN

Reported on 40 benchmarks across 4 tasks · 1 paper · 24 SOTA

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

Computer Vision20 results

Image Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
FID· 2016-08-01
139.78
best: 5.36 (HiFaceGAN)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
Image Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
MS-SSIM· 2016-08-01
0.93
best: 0.971 (HiFaceGAN)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
Image Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
SSIM· 2016-08-01
0.709
best: 0.816 (HiFaceGAN)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
Image Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
FID· 2016-08-01
23.97
best: 1.978 (HiFaceGAN)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
Image Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
MS-SSIM· 2016-08-01
0.951
best: 0.975 (HiFaceGAN)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
Image Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
SSIM· 2016-08-01
0.804
best: 0.906 (CAGFace)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
3D Object Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
FID· 2016-08-01
139.78
best: 5.36 (HiFaceGAN)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
3D Object Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
MS-SSIM· 2016-08-01
0.93
best: 0.971 (HiFaceGAN)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
3D Object Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
SSIM· 2016-08-01
0.709
best: 0.816 (HiFaceGAN)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
3D Object Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
FID· 2016-08-01
23.97
best: 1.978 (HiFaceGAN)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
3D Object Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
MS-SSIM· 2016-08-01
0.951
best: 0.975 (HiFaceGAN)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
3D Object Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
SSIM· 2016-08-01
0.804
best: 0.906 (CAGFace)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
Image Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
PSNR· 2016-08-01
22.45
best: 28.65 (HiFaceGAN)
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
Image Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
PSNR· 2016-08-01
24.71
best: 34.1 (CAGFace)
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
Image Super-ResolutiononManga109 - 4x upscaling
PSNR· 2016-08-01
27.9
best: 33.19 (HMA†)
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
Image Super-ResolutiononManga109 - 4x upscaling
SSIM· 2016-08-01
0.861
best: 0.9366 (Hi-IR-L)
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
3D Object Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
PSNR· 2016-08-01
22.45
best: 28.65 (HiFaceGAN)
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
3D Object Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
PSNR· 2016-08-01
24.71
best: 34.1 (CAGFace)
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
3D Object Super-ResolutiononManga109 - 4x upscaling
PSNR· 2016-08-01
27.9
best: 33.19 (HMA†)
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
3D Object Super-ResolutiononManga109 - 4x upscaling
SSIM· 2016-08-01
0.861
best: 0.9366 (Hi-IR-L)
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367

Graphs10 results

Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
FID· 2016-08-01
139.78
best: 5.36 (HiFaceGAN)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
MS-SSIM· 2016-08-01
0.93
best: 0.971 (HiFaceGAN)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
SSIM· 2016-08-01
0.709
best: 0.816 (HiFaceGAN)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
FID· 2016-08-01
23.97
best: 1.978 (HiFaceGAN)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
MS-SSIM· 2016-08-01
0.951
best: 0.975 (HiFaceGAN)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
SSIM· 2016-08-01
0.804
best: 0.906 (CAGFace)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
PSNR· 2016-08-01
22.45
best: 28.65 (HiFaceGAN)
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
PSNR· 2016-08-01
24.71
best: 34.1 (CAGFace)
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
Super-ResolutiononManga109 - 4x upscaling
PSNR· 2016-08-01
27.9
best: 33.19 (HMA†)
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
Super-ResolutiononManga109 - 4x upscaling
SSIM· 2016-08-01
0.861
best: 0.9366 (Hi-IR-L)
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367

Methodology10 results

16konFFHQ 256 x 256 - 4x upscaling
FID· 2016-08-01
139.78
best: 5.36 (HiFaceGAN)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
16konFFHQ 256 x 256 - 4x upscaling
MS-SSIM· 2016-08-01
0.93
best: 0.971 (HiFaceGAN)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
16konFFHQ 256 x 256 - 4x upscaling
SSIM· 2016-08-01
0.709
best: 0.816 (HiFaceGAN)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
16konFFHQ 1024 x 1024 - 4x upscaling
FID· 2016-08-01
23.97
best: 1.978 (HiFaceGAN)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
16konFFHQ 1024 x 1024 - 4x upscaling
MS-SSIM· 2016-08-01
0.951
best: 0.975 (HiFaceGAN)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
16konFFHQ 1024 x 1024 - 4x upscaling
SSIM· 2016-08-01
0.804
best: 0.906 (CAGFace)
SOTA
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
16konFFHQ 256 x 256 - 4x upscaling
PSNR· 2016-08-01
22.45
best: 28.65 (HiFaceGAN)
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
16konFFHQ 1024 x 1024 - 4x upscaling
PSNR· 2016-08-01
24.71
best: 34.1 (CAGFace)
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
16konManga109 - 4x upscaling
PSNR· 2016-08-01
27.9
best: 33.19 (HMA†)
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367
16konManga109 - 4x upscaling
SSIM· 2016-08-01
0.861
best: 0.9366 (Hi-IR-L)
Accelerating the Super-Resolution Convolutional Neural Network arXiv:1608.00367