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Models/GMFN

GMFN

Reported on 32 benchmarks across 4 tasks · 1 paper

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

Computer Vision16 results

Image Super-ResolutiononSet14 - 4x upscaling
PSNR· 2019-07-09
28.84
best: 29.54 (DRCT-L)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
Image Super-ResolutiononSet14 - 4x upscaling
SSIM· 2019-07-09
0.7888
best: 0.894 (Edge-informed SR)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
Image Super-ResolutiononManga109 - 4x upscaling
PSNR· 2019-07-09
31.24
best: 33.19 (HMA†)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
Image Super-ResolutiononManga109 - 4x upscaling
SSIM· 2019-07-09
0.9174
best: 0.9366 (Hi-IR-L)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
Image Super-ResolutiononUrban100 - 4x upscaling
PSNR· 2019-07-09
26.69
best: 28.72 (Hi-IR-L)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
Image Super-ResolutiononUrban100 - 4x upscaling
SSIM· 2019-07-09
0.8048
best: 0.9481 (SPSR)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
Image Super-ResolutiononBSD100 - 4x upscaling
PSNR· 2019-07-09
27.74
best: 28.16 (DRCT-L)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
Image Super-ResolutiononBSD100 - 4x upscaling
SSIM· 2019-07-09
0.7421
best: 0.851 (Edge-informed SR)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
3D Object Super-ResolutiononSet14 - 4x upscaling
PSNR· 2019-07-09
28.84
best: 29.54 (DRCT-L)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
3D Object Super-ResolutiononSet14 - 4x upscaling
SSIM· 2019-07-09
0.7888
best: 0.894 (Edge-informed SR)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
3D Object Super-ResolutiononManga109 - 4x upscaling
PSNR· 2019-07-09
31.24
best: 33.19 (HMA†)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
3D Object Super-ResolutiononManga109 - 4x upscaling
SSIM· 2019-07-09
0.9174
best: 0.9366 (Hi-IR-L)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
3D Object Super-ResolutiononUrban100 - 4x upscaling
PSNR· 2019-07-09
26.69
best: 28.72 (Hi-IR-L)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
3D Object Super-ResolutiononUrban100 - 4x upscaling
SSIM· 2019-07-09
0.8048
best: 0.9481 (SPSR)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
3D Object Super-ResolutiononBSD100 - 4x upscaling
PSNR· 2019-07-09
27.74
best: 28.16 (DRCT-L)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
3D Object Super-ResolutiononBSD100 - 4x upscaling
SSIM· 2019-07-09
0.7421
best: 0.851 (Edge-informed SR)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253

Graphs8 results

Super-ResolutiononSet14 - 4x upscaling
PSNR· 2019-07-09
28.84
best: 29.54 (DRCT-L)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
Super-ResolutiononSet14 - 4x upscaling
SSIM· 2019-07-09
0.7888
best: 0.894 (Edge-informed SR)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
Super-ResolutiononManga109 - 4x upscaling
PSNR· 2019-07-09
31.24
best: 33.19 (HMA†)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
Super-ResolutiononManga109 - 4x upscaling
SSIM· 2019-07-09
0.9174
best: 0.9366 (Hi-IR-L)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
Super-ResolutiononUrban100 - 4x upscaling
PSNR· 2019-07-09
26.69
best: 28.72 (Hi-IR-L)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
Super-ResolutiononUrban100 - 4x upscaling
SSIM· 2019-07-09
0.8048
best: 0.9481 (SPSR)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
Super-ResolutiononBSD100 - 4x upscaling
PSNR· 2019-07-09
27.74
best: 28.16 (DRCT-L)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
Super-ResolutiononBSD100 - 4x upscaling
SSIM· 2019-07-09
0.7421
best: 0.851 (Edge-informed SR)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253

Methodology8 results

16konSet14 - 4x upscaling
PSNR· 2019-07-09
28.84
best: 29.54 (DRCT-L)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
16konSet14 - 4x upscaling
SSIM· 2019-07-09
0.7888
best: 0.894 (Edge-informed SR)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
16konManga109 - 4x upscaling
PSNR· 2019-07-09
31.24
best: 33.19 (HMA†)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
16konManga109 - 4x upscaling
SSIM· 2019-07-09
0.9174
best: 0.9366 (Hi-IR-L)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
16konUrban100 - 4x upscaling
PSNR· 2019-07-09
26.69
best: 28.72 (Hi-IR-L)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
16konUrban100 - 4x upscaling
SSIM· 2019-07-09
0.8048
best: 0.9481 (SPSR)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
16konBSD100 - 4x upscaling
PSNR· 2019-07-09
27.74
best: 28.16 (DRCT-L)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253
16konBSD100 - 4x upscaling
SSIM· 2019-07-09
0.7421
best: 0.851 (Edge-informed SR)
Gated Multiple Feedback Network for Image Super-Resolution arXiv:1907.04253