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Models/RCAN

RCAN

Reported on 32 benchmarks across 4 tasks · 1 paper · 12 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-ResolutiononManga109 - 4x upscaling
PSNR· 2018-07-08
31.22
best: 33.19 (HMA†)
SOTA
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
Image Super-ResolutiononManga109 - 4x upscaling
SSIM· 2018-07-08
0.9173
best: 0.9366 (Hi-IR-L)
SOTA
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
Image Super-ResolutiononUrban100 - 4x upscaling
SSIM· 2018-07-08
0.8087
best: 0.9481 (SPSR)
SOTA
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
3D Object Super-ResolutiononManga109 - 4x upscaling
PSNR· 2018-07-08
31.22
best: 33.19 (HMA†)
SOTA
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
3D Object Super-ResolutiononManga109 - 4x upscaling
SSIM· 2018-07-08
0.9173
best: 0.9366 (Hi-IR-L)
SOTA
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
3D Object Super-ResolutiononUrban100 - 4x upscaling
SSIM· 2018-07-08
0.8087
best: 0.9481 (SPSR)
SOTA
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
Image Super-ResolutiononSet14 - 4x upscaling
PSNR· 2018-07-08
28.87
best: 29.54 (DRCT-L)
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
Image Super-ResolutiononSet14 - 4x upscaling
SSIM· 2018-07-08
0.7889
best: 0.894 (Edge-informed SR)
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
Image Super-ResolutiononUrban100 - 4x upscaling
PSNR· 2018-07-08
26.82
best: 28.72 (Hi-IR-L)
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
Image Super-ResolutiononBSD100 - 4x upscaling
PSNR· 2018-07-08
27.77
best: 28.16 (DRCT-L)
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
Image Super-ResolutiononBSD100 - 4x upscaling
SSIM· 2018-07-08
0.7436
best: 0.851 (Edge-informed SR)
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
3D Object Super-ResolutiononSet14 - 4x upscaling
PSNR· 2018-07-08
28.87
best: 29.54 (DRCT-L)
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
3D Object Super-ResolutiononSet14 - 4x upscaling
SSIM· 2018-07-08
0.7889
best: 0.894 (Edge-informed SR)
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
3D Object Super-ResolutiononUrban100 - 4x upscaling
PSNR· 2018-07-08
26.82
best: 28.72 (Hi-IR-L)
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
3D Object Super-ResolutiononBSD100 - 4x upscaling
PSNR· 2018-07-08
27.77
best: 28.16 (DRCT-L)
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
3D Object Super-ResolutiononBSD100 - 4x upscaling
SSIM· 2018-07-08
0.7436
best: 0.851 (Edge-informed SR)
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758

Graphs8 results

Super-ResolutiononManga109 - 4x upscaling
PSNR· 2018-07-08
31.22
best: 33.19 (HMA†)
SOTA
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
Super-ResolutiononManga109 - 4x upscaling
SSIM· 2018-07-08
0.9173
best: 0.9366 (Hi-IR-L)
SOTA
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
Super-ResolutiononUrban100 - 4x upscaling
SSIM· 2018-07-08
0.8087
best: 0.9481 (SPSR)
SOTA
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
Super-ResolutiononSet14 - 4x upscaling
PSNR· 2018-07-08
28.87
best: 29.54 (DRCT-L)
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
Super-ResolutiononSet14 - 4x upscaling
SSIM· 2018-07-08
0.7889
best: 0.894 (Edge-informed SR)
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
Super-ResolutiononUrban100 - 4x upscaling
PSNR· 2018-07-08
26.82
best: 28.72 (Hi-IR-L)
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
Super-ResolutiononBSD100 - 4x upscaling
PSNR· 2018-07-08
27.77
best: 28.16 (DRCT-L)
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
Super-ResolutiononBSD100 - 4x upscaling
SSIM· 2018-07-08
0.7436
best: 0.851 (Edge-informed SR)
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758

Methodology8 results

16konManga109 - 4x upscaling
PSNR· 2018-07-08
31.22
best: 33.19 (HMA†)
SOTA
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
16konManga109 - 4x upscaling
SSIM· 2018-07-08
0.9173
best: 0.9366 (Hi-IR-L)
SOTA
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
16konUrban100 - 4x upscaling
SSIM· 2018-07-08
0.8087
best: 0.9481 (SPSR)
SOTA
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
16konSet14 - 4x upscaling
PSNR· 2018-07-08
28.87
best: 29.54 (DRCT-L)
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
16konSet14 - 4x upscaling
SSIM· 2018-07-08
0.7889
best: 0.894 (Edge-informed SR)
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
16konUrban100 - 4x upscaling
PSNR· 2018-07-08
26.82
best: 28.72 (Hi-IR-L)
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
16konBSD100 - 4x upscaling
PSNR· 2018-07-08
27.77
best: 28.16 (DRCT-L)
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758
16konBSD100 - 4x upscaling
SSIM· 2018-07-08
0.7436
best: 0.851 (Edge-informed SR)
Image Super-Resolution Using Very Deep Residual Channel Attention Networks arXiv:1807.02758