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Models/GRDN

GRDN

Reported on 6 benchmarks across 3 tasks · 1 paper · 4 SOTA

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

Computer Vision2 results

DenoisingonNTIRE 2019 Real Image Denoising Challenge (sRGB)
PSNR· 2019-05-27
39.931743
SOTA
GRDN:Grouped Residual Dense Network for Real Image Denoising and GAN-based Real-world Noise Modeling arXiv:1905.11172
DenoisingonNTIRE 2019 Real Image Denoising Challenge (sRGB)
SSIM· 2019-05-27
0.973589
SOTA
GRDN:Grouped Residual Dense Network for Real Image Denoising and GAN-based Real-world Noise Modeling arXiv:1905.11172

Adversarial2 results

3D ArchitectureonNTIRE 2019 Real Image Denoising Challenge (sRGB)
PSNR· 2019-05-27
39.931743
SOTA
GRDN:Grouped Residual Dense Network for Real Image Denoising and GAN-based Real-world Noise Modeling arXiv:1905.11172
3D ArchitectureonNTIRE 2019 Real Image Denoising Challenge (sRGB)
SSIM· 2019-05-27
0.973589
SOTA
GRDN:Grouped Residual Dense Network for Real Image Denoising and GAN-based Real-world Noise Modeling arXiv:1905.11172

Medical2 results

Noise EstimationonSIDD
Average KL Divergence· 2019-05-27
0.443
best: 0.728 (CBDNet)
GRDN:Grouped Residual Dense Network for Real Image Denoising and GAN-based Real-world Noise Modeling arXiv:1905.11172
Noise EstimationonSIDD
PSNR Gap· 2019-05-27
2.28
best: 8.3 (CBDNet)
GRDN:Grouped Residual Dense Network for Real Image Denoising and GAN-based Real-world Noise Modeling arXiv:1905.11172