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Models/CAGFace

CAGFace

Reported on 32 benchmarks across 4 tasks · 1 paper · 32 SOTA

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

Computer Vision16 results

Image Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
FID· 2019-10-19
74.43
best: 5.36 (HiFaceGAN)
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
Image Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
MS-SSIM· 2019-10-19
0.958
best: 0.971 (HiFaceGAN)
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
Image Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
PSNR· 2019-10-19
27.42
best: 28.65 (HiFaceGAN)
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
Image Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
SSIM· 2019-10-19
0.816
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
Image Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
FID· 2019-10-19
12.4
best: 1.978 (HiFaceGAN)
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
Image Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
MS-SSIM· 2019-10-19
0.971
best: 0.975 (HiFaceGAN)
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
Image Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
PSNR· 2019-10-19
34.1
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
Image Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
SSIM· 2019-10-19
0.906
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
3D Object Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
FID· 2019-10-19
74.43
best: 5.36 (HiFaceGAN)
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
3D Object Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
MS-SSIM· 2019-10-19
0.958
best: 0.971 (HiFaceGAN)
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
3D Object Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
PSNR· 2019-10-19
27.42
best: 28.65 (HiFaceGAN)
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
3D Object Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
SSIM· 2019-10-19
0.816
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
3D Object Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
FID· 2019-10-19
12.4
best: 1.978 (HiFaceGAN)
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
3D Object Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
MS-SSIM· 2019-10-19
0.971
best: 0.975 (HiFaceGAN)
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
3D Object Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
PSNR· 2019-10-19
34.1
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
3D Object Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
SSIM· 2019-10-19
0.906
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761

Graphs8 results

Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
FID· 2019-10-19
74.43
best: 5.36 (HiFaceGAN)
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
MS-SSIM· 2019-10-19
0.958
best: 0.971 (HiFaceGAN)
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
PSNR· 2019-10-19
27.42
best: 28.65 (HiFaceGAN)
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
SSIM· 2019-10-19
0.816
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
FID· 2019-10-19
12.4
best: 1.978 (HiFaceGAN)
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
MS-SSIM· 2019-10-19
0.971
best: 0.975 (HiFaceGAN)
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
PSNR· 2019-10-19
34.1
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
SSIM· 2019-10-19
0.906
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761

Methodology8 results

16konFFHQ 256 x 256 - 4x upscaling
FID· 2019-10-19
74.43
best: 5.36 (HiFaceGAN)
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
16konFFHQ 256 x 256 - 4x upscaling
MS-SSIM· 2019-10-19
0.958
best: 0.971 (HiFaceGAN)
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
16konFFHQ 256 x 256 - 4x upscaling
PSNR· 2019-10-19
27.42
best: 28.65 (HiFaceGAN)
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
16konFFHQ 256 x 256 - 4x upscaling
SSIM· 2019-10-19
0.816
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
16konFFHQ 1024 x 1024 - 4x upscaling
FID· 2019-10-19
12.4
best: 1.978 (HiFaceGAN)
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
16konFFHQ 1024 x 1024 - 4x upscaling
MS-SSIM· 2019-10-19
0.971
best: 0.975 (HiFaceGAN)
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
16konFFHQ 1024 x 1024 - 4x upscaling
PSNR· 2019-10-19
34.1
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761
16konFFHQ 1024 x 1024 - 4x upscaling
SSIM· 2019-10-19
0.906
SOTA
Component Attention Guided Face Super-Resolution Network: CAGFace arXiv:1910.08761