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Models/VTGAN

VTGAN

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

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

Computer Vision2 results

  • Image-to-Image TranslationonFundus Fluorescein Angiogram Photographs & Colour Fundus Images of Diabetic Patients
    FID· 2021-04-14
    17.3
    SOTA
    VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision TransformersarXiv:2104.06757
  • Image-to-Image TranslationonFundus Fluorescein Angiogram Photographs & Colour Fundus Images of Diabetic Patients
    Kernel Inception Distance· 2021-04-14
    0.00053
    best: 0.00595 (Attention2Angio w/o Perceptual Loss + Feature Matching Loss)
    VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision TransformersarXiv:2104.06757

Medical2 results

  • Image GenerationonFundus Fluorescein Angiogram Photographs & Colour Fundus Images of Diabetic Patients
    FID· 2021-04-14
    17.3
    SOTA
    VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision TransformersarXiv:2104.06757
  • Image GenerationonFundus Fluorescein Angiogram Photographs & Colour Fundus Images of Diabetic Patients
    Kernel Inception Distance· 2021-04-14
    0.00053
    best: 0.00595 (Attention2Angio w/o Perceptual Loss + Feature Matching Loss)
    VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision TransformersarXiv:2104.06757

Miscellaneous2 results

  • 1 Image, 2*2 StitchingonFundus Fluorescein Angiogram Photographs & Colour Fundus Images of Diabetic Patients
    FID· 2021-04-14
    17.3
    SOTA
    VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision TransformersarXiv:2104.06757
  • 1 Image, 2*2 StitchingonFundus Fluorescein Angiogram Photographs & Colour Fundus Images of Diabetic Patients
    Kernel Inception Distance· 2021-04-14
    0.00053
    best: 0.00595 (Attention2Angio w/o Perceptual Loss + Feature Matching Loss)
    VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision TransformersarXiv:2104.06757