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Models/RIDNet

RIDNet

Reported on 20 benchmarks across 3 tasks · 1 paper · 16 SOTA

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

Computer Vision10 results

  • DenoisingonSIDD
    PSNR (sRGB)· uses extra data· 2019-04-16
    38.71
    best: 40.39 (CGNet)
    SOTA
    Real Image Denoising with Feature AttentionarXiv:1904.07396
  • DenoisingonSIDD
    SSIM (sRGB)· uses extra data· 2019-04-16
    0.951
    best: 0.973 (NBNet)
    SOTA
    Real Image Denoising with Feature AttentionarXiv:1904.07396
  • DenoisingonDND
    PSNR (sRGB)· uses extra data· 2019-04-16
    39.26
    best: 40.594 (DualDn)
    SOTA
    Real Image Denoising with Feature AttentionarXiv:1904.07396
  • DenoisingonDND
    SSIM (sRGB)· uses extra data· 2019-04-16
    0.953
    best: 0.966 (DualDn)
    SOTA
    Real Image Denoising with Feature AttentionarXiv:1904.07396
  • DenoisingonBSD68 sigma15
    PSNR· 2019-04-16
    34.01
    SOTA
    Real Image Denoising with Feature AttentionarXiv:1904.07396
  • DenoisingonBSD68 sigma25
    PSNR· 2019-04-16
    31.37
    SOTA
    Real Image Denoising with Feature AttentionarXiv:1904.07396
  • DenoisingonCBSD68 sigma50
    PSNR· 2019-04-16
    28.14
    best: 29.39 (IPT)
    Real Image Denoising with Feature AttentionarXiv:1904.07396
  • DenoisingonBSD68 sigma15
    PSNR· 2019-04-16
    31.81
    best: 34.01
    Real Image Denoising with Feature AttentionarXiv:1904.07396
  • DenoisingonBSD68 sigma25
    PSNR· 2019-04-16
    29.34
    best: 31.37
    Real Image Denoising with Feature AttentionarXiv:1904.07396
  • DenoisingonBSD68 sigma50
    PSNR· 2019-04-16
    26.4
    best: 30.08 (MaIR+)
    Real Image Denoising with Feature AttentionarXiv:1904.07396

Adversarial10 results

  • 3D ArchitectureonSIDD
    PSNR (sRGB)· uses extra data· 2019-04-16
    38.71
    best: 40.39 (CGNet)
    SOTA
    Real Image Denoising with Feature AttentionarXiv:1904.07396
  • 3D ArchitectureonSIDD
    SSIM (sRGB)· uses extra data· 2019-04-16
    0.951
    best: 0.973 (NBNet)
    SOTA
    Real Image Denoising with Feature AttentionarXiv:1904.07396
  • 3D ArchitectureonDND
    PSNR (sRGB)· uses extra data· 2019-04-16
    39.26
    best: 40.594 (DualDn)
    SOTA
    Real Image Denoising with Feature AttentionarXiv:1904.07396
  • 3D ArchitectureonDND
    SSIM (sRGB)· uses extra data· 2019-04-16
    0.953
    best: 0.966 (DualDn)
    SOTA
    Real Image Denoising with Feature AttentionarXiv:1904.07396
  • 3D ArchitectureonBSD68 sigma15
    PSNR· 2019-04-16
    34.01
    SOTA
    Real Image Denoising with Feature AttentionarXiv:1904.07396
  • 3D ArchitectureonBSD68 sigma25
    PSNR· 2019-04-16
    31.37
    SOTA
    Real Image Denoising with Feature AttentionarXiv:1904.07396
  • 3D ArchitectureonCBSD68 sigma50
    PSNR· 2019-04-16
    28.14
    best: 29.39 (IPT)
    Real Image Denoising with Feature AttentionarXiv:1904.07396
  • 3D ArchitectureonBSD68 sigma15
    PSNR· 2019-04-16
    31.81
    best: 34.01
    Real Image Denoising with Feature AttentionarXiv:1904.07396
  • 3D ArchitectureonBSD68 sigma25
    PSNR· 2019-04-16
    29.34
    best: 31.37
    Real Image Denoising with Feature AttentionarXiv:1904.07396
  • 3D ArchitectureonBSD68 sigma50
    PSNR· 2019-04-16
    26.4
    best: 30.08 (MaIR+)
    Real Image Denoising with Feature AttentionarXiv:1904.07396

Medical4 results

  • Image DenoisingonSIDD
    PSNR (sRGB)· uses extra data· 2019-04-16
    38.71
    best: 40.39 (CGNet)
    SOTA
    Real Image Denoising with Feature AttentionarXiv:1904.07396
  • Image DenoisingonSIDD
    SSIM (sRGB)· uses extra data· 2019-04-16
    0.951
    best: 0.973 (NBNet)
    SOTA
    Real Image Denoising with Feature AttentionarXiv:1904.07396
  • Image DenoisingonDND
    PSNR (sRGB)· uses extra data· 2019-04-16
    39.26
    best: 40.594 (DualDn)
    SOTA
    Real Image Denoising with Feature AttentionarXiv:1904.07396
  • Image DenoisingonDND
    SSIM (sRGB)· uses extra data· 2019-04-16
    0.953
    best: 0.966 (DualDn)
    SOTA
    Real Image Denoising with Feature AttentionarXiv:1904.07396