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Models/SRCNN

SRCNN

Reported on 180 benchmarks across 15 tasks · 3 papers · 178 SOTA

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

Computer Vision84 results

3D Human Pose EstimationonMSU Video Upscalers: Quality Enhancement
PSNR· 2014-12-31
26.68
best: 31.28 (VEAI-AHQ-12)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Human Pose EstimationonMSU Video Upscalers: Quality Enhancement
SSIM· 2014-12-31
0.929
best: 0.939 (iSeeBetter)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Human Pose EstimationonMSU Video Upscalers: Quality Enhancement
VMAF· 2014-12-31
51.21
best: 61.2 (TecoGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Human Pose EstimationonUltra Video Group HD - 4x upscaling
Average PSNR· 2014-12-31
37.52
best: 48.23 (RAMS (ours))
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Human Pose EstimationonXiph HD - 4x upscaling
Average PSNR· 2014-12-31
31.47
best: 31.67 (ESPCN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Human Pose EstimationonVid4 - 4x upscaling
MOVIE· 2014-12-31
6.9
best: 9.31 (bicubic)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Human Pose EstimationonVid4 - 4x upscaling
PSNR· 2014-12-31
24.68
best: 31.36 (NeuriCam-net)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Human Pose EstimationonVid4 - 4x upscaling
SSIM· 2014-12-31
0.7158
best: 0.933 (NeuriCam-net)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
VideoonMSU Video Upscalers: Quality Enhancement
PSNR· 2014-12-31
26.68
best: 31.28 (VEAI-AHQ-12)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
VideoonMSU Video Upscalers: Quality Enhancement
SSIM· 2014-12-31
0.929
best: 0.939 (iSeeBetter)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
VideoonMSU Video Upscalers: Quality Enhancement
VMAF· 2014-12-31
51.21
best: 61.2 (TecoGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
VideoonUltra Video Group HD - 4x upscaling
Average PSNR· 2014-12-31
37.52
best: 48.23 (RAMS (ours))
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
VideoonXiph HD - 4x upscaling
Average PSNR· 2014-12-31
31.47
best: 31.67 (ESPCN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
VideoonVid4 - 4x upscaling
MOVIE· 2014-12-31
6.9
best: 9.31 (bicubic)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
VideoonVid4 - 4x upscaling
PSNR· 2014-12-31
24.68
best: 31.36 (NeuriCam-net)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
VideoonVid4 - 4x upscaling
SSIM· 2014-12-31
0.7158
best: 0.933 (NeuriCam-net)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Pose EstimationonMSU Video Upscalers: Quality Enhancement
PSNR· 2014-12-31
26.68
best: 31.28 (VEAI-AHQ-12)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Pose EstimationonMSU Video Upscalers: Quality Enhancement
SSIM· 2014-12-31
0.929
best: 0.939 (iSeeBetter)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Pose EstimationonMSU Video Upscalers: Quality Enhancement
VMAF· 2014-12-31
51.21
best: 61.2 (TecoGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Pose EstimationonUltra Video Group HD - 4x upscaling
Average PSNR· 2014-12-31
37.52
best: 48.23 (RAMS (ours))
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Pose EstimationonXiph HD - 4x upscaling
Average PSNR· 2014-12-31
31.47
best: 31.67 (ESPCN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Pose EstimationonVid4 - 4x upscaling
MOVIE· 2014-12-31
6.9
best: 9.31 (bicubic)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Pose EstimationonVid4 - 4x upscaling
PSNR· 2014-12-31
24.68
best: 31.36 (NeuriCam-net)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Pose EstimationonVid4 - 4x upscaling
SSIM· 2014-12-31
0.7158
best: 0.933 (NeuriCam-net)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Image Super-ResolutiononSet5 - 4x upscaling
PSNR· 2014-12-31
30.49
best: 33.38 (HMA†)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Image Super-ResolutiononSet5 - 4x upscaling
SSIM· 2014-12-31
0.8628
best: 0.9103 (Hi-IR-L)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Image Super-ResolutiononSet14 - 4x upscaling
PSNR· 2014-12-31
27.5
best: 29.54 (DRCT-L)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Image Super-ResolutiononSet14 - 4x upscaling
SSIM· 2014-12-31
0.7513
best: 0.894 (Edge-informed SR)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Image Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
FID· 2014-12-31
147.21
best: 5.36 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Image Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
MS-SSIM· 2014-12-31
0.9
best: 0.971 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Image Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
PSNR· 2014-12-31
23.12
best: 28.65 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Image Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
SSIM· 2014-12-31
0.688
best: 0.816 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Image Super-ResolutiononIXI
PSNR 2x T2w· 2014-12-31
37.32
best: 40.43 (EDSR+MMHCA)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Image Super-ResolutiononIXI
PSNR 4x T2w· 2014-12-31
29.69
best: 32.7 (EDSR+MMHCA)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Image Super-ResolutiononIXI
SSIM 4x T2w· 2014-12-31
0.9052
best: 0.9472 (SERAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Image Super-ResolutiononIXI
SSIM for 2x T2w· 2014-12-31
0.9796
best: 0.9877 (EDSR+MMHCA)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Image Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
FID· 2014-12-31
31.84
best: 1.978 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Image Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
MS-SSIM· 2014-12-31
0.924
best: 0.975 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Image Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
PSNR· 2014-12-31
27.4
best: 34.1 (CAGFace)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Image Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
SSIM· 2014-12-31
0.801
best: 0.906 (CAGFace)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Image Super-ResolutiononManga109 - 4x upscaling
PSNR· 2014-12-31
27.58
best: 33.19 (HMA†)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Image Super-ResolutiononManga109 - 4x upscaling
SSIM· 2014-12-31
0.8555
best: 0.9366 (Hi-IR-L)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Image Super-ResolutiononUrban100 - 4x upscaling
PSNR· 2014-12-31
24.52
best: 28.72 (Hi-IR-L)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Image Super-ResolutiononUrban100 - 4x upscaling
SSIM· 2014-12-31
0.7221
best: 0.9481 (SPSR)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Image Super-ResolutiononBSD100 - 4x upscaling
PSNR· 2014-12-31
26.9
best: 28.16 (DRCT-L)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Image Super-ResolutiononBSD100 - 4x upscaling
SSIM· 2014-12-31
0.7101
best: 0.851 (Edge-informed SR)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Video Super-ResolutiononMSU Video Upscalers: Quality Enhancement
PSNR· 2014-12-31
26.68
best: 31.28 (VEAI-AHQ-12)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Video Super-ResolutiononMSU Video Upscalers: Quality Enhancement
SSIM· 2014-12-31
0.929
best: 0.939 (iSeeBetter)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Video Super-ResolutiononMSU Video Upscalers: Quality Enhancement
VMAF· 2014-12-31
51.21
best: 61.2 (TecoGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Video Super-ResolutiononUltra Video Group HD - 4x upscaling
Average PSNR· 2014-12-31
37.52
best: 48.23 (RAMS (ours))
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Video Super-ResolutiononXiph HD - 4x upscaling
Average PSNR· 2014-12-31
31.47
best: 31.67 (ESPCN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Video Super-ResolutiononVid4 - 4x upscaling
MOVIE· 2014-12-31
6.9
best: 9.31 (bicubic)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Video Super-ResolutiononVid4 - 4x upscaling
PSNR· 2014-12-31
24.68
best: 31.36 (NeuriCam-net)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Video Super-ResolutiononVid4 - 4x upscaling
SSIM· 2014-12-31
0.7158
best: 0.933 (NeuriCam-net)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononSet5 - 4x upscaling
PSNR· 2014-12-31
30.49
best: 33.38 (HMA†)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononSet5 - 4x upscaling
SSIM· 2014-12-31
0.8628
best: 0.9103 (Hi-IR-L)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononSet14 - 4x upscaling
PSNR· 2014-12-31
27.5
best: 29.54 (DRCT-L)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononSet14 - 4x upscaling
SSIM· 2014-12-31
0.7513
best: 0.894 (Edge-informed SR)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
FID· 2014-12-31
147.21
best: 5.36 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
MS-SSIM· 2014-12-31
0.9
best: 0.971 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
PSNR· 2014-12-31
23.12
best: 28.65 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
SSIM· 2014-12-31
0.688
best: 0.816 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononIXI
PSNR 2x T2w· 2014-12-31
37.32
best: 40.43 (EDSR+MMHCA)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononIXI
PSNR 4x T2w· 2014-12-31
29.69
best: 32.7 (EDSR+MMHCA)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononIXI
SSIM 4x T2w· 2014-12-31
0.9052
best: 0.9472 (SERAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononIXI
SSIM for 2x T2w· 2014-12-31
0.9796
best: 0.9877 (EDSR+MMHCA)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
FID· 2014-12-31
31.84
best: 1.978 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
MS-SSIM· 2014-12-31
0.924
best: 0.975 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
PSNR· 2014-12-31
27.4
best: 34.1 (CAGFace)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
SSIM· 2014-12-31
0.801
best: 0.906 (CAGFace)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononManga109 - 4x upscaling
PSNR· 2014-12-31
27.58
best: 33.19 (HMA†)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononManga109 - 4x upscaling
SSIM· 2014-12-31
0.8555
best: 0.9366 (Hi-IR-L)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononUrban100 - 4x upscaling
PSNR· 2014-12-31
24.52
best: 28.72 (Hi-IR-L)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononUrban100 - 4x upscaling
SSIM· 2014-12-31
0.7221
best: 0.9481 (SPSR)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononBSD100 - 4x upscaling
PSNR· 2014-12-31
26.9
best: 28.16 (DRCT-L)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononBSD100 - 4x upscaling
SSIM· 2014-12-31
0.7101
best: 0.851 (Edge-informed SR)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononMSU Video Upscalers: Quality Enhancement
PSNR· 2014-12-31
26.68
best: 31.28 (VEAI-AHQ-12)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononMSU Video Upscalers: Quality Enhancement
SSIM· 2014-12-31
0.929
best: 0.939 (iSeeBetter)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononMSU Video Upscalers: Quality Enhancement
VMAF· 2014-12-31
51.21
best: 61.2 (TecoGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononUltra Video Group HD - 4x upscaling
Average PSNR· 2014-12-31
37.52
best: 48.23 (RAMS (ours))
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononXiph HD - 4x upscaling
Average PSNR· 2014-12-31
31.47
best: 31.67 (ESPCN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononVid4 - 4x upscaling
MOVIE· 2014-12-31
6.9
best: 9.31 (bicubic)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononVid4 - 4x upscaling
PSNR· 2014-12-31
24.68
best: 31.36 (NeuriCam-net)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Object Super-ResolutiononVid4 - 4x upscaling
SSIM· 2014-12-31
0.7158
best: 0.933 (NeuriCam-net)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092

Methodology31 results

3DonMSU Video Upscalers: Quality Enhancement
PSNR· 2014-12-31
26.68
best: 31.28 (VEAI-AHQ-12)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3DonMSU Video Upscalers: Quality Enhancement
SSIM· 2014-12-31
0.929
best: 0.939 (iSeeBetter)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3DonMSU Video Upscalers: Quality Enhancement
VMAF· 2014-12-31
51.21
best: 61.2 (TecoGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3DonUltra Video Group HD - 4x upscaling
Average PSNR· 2014-12-31
37.52
best: 48.23 (RAMS (ours))
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3DonXiph HD - 4x upscaling
Average PSNR· 2014-12-31
31.47
best: 31.67 (ESPCN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3DonVid4 - 4x upscaling
MOVIE· 2014-12-31
6.9
best: 9.31 (bicubic)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3DonVid4 - 4x upscaling
PSNR· 2014-12-31
24.68
best: 31.36 (NeuriCam-net)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3DonVid4 - 4x upscaling
SSIM· 2014-12-31
0.7158
best: 0.933 (NeuriCam-net)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
16konSet5 - 4x upscaling
PSNR· 2014-12-31
30.49
best: 33.38 (HMA†)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
16konSet5 - 4x upscaling
SSIM· 2014-12-31
0.8628
best: 0.9103 (Hi-IR-L)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
16konSet14 - 4x upscaling
PSNR· 2014-12-31
27.5
best: 29.54 (DRCT-L)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
16konSet14 - 4x upscaling
SSIM· 2014-12-31
0.7513
best: 0.894 (Edge-informed SR)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
16konFFHQ 256 x 256 - 4x upscaling
FID· 2014-12-31
147.21
best: 5.36 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
16konFFHQ 256 x 256 - 4x upscaling
MS-SSIM· 2014-12-31
0.9
best: 0.971 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
16konFFHQ 256 x 256 - 4x upscaling
PSNR· 2014-12-31
23.12
best: 28.65 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
16konFFHQ 256 x 256 - 4x upscaling
SSIM· 2014-12-31
0.688
best: 0.816 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
16konIXI
PSNR 2x T2w· 2014-12-31
37.32
best: 40.43 (EDSR+MMHCA)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
16konIXI
PSNR 4x T2w· 2014-12-31
29.69
best: 32.7 (EDSR+MMHCA)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
16konIXI
SSIM 4x T2w· 2014-12-31
0.9052
best: 0.9472 (SERAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
16konIXI
SSIM for 2x T2w· 2014-12-31
0.9796
best: 0.9877 (EDSR+MMHCA)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
16konFFHQ 1024 x 1024 - 4x upscaling
FID· 2014-12-31
31.84
best: 1.978 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
16konFFHQ 1024 x 1024 - 4x upscaling
MS-SSIM· 2014-12-31
0.924
best: 0.975 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
16konFFHQ 1024 x 1024 - 4x upscaling
PSNR· 2014-12-31
27.4
best: 34.1 (CAGFace)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
16konFFHQ 1024 x 1024 - 4x upscaling
SSIM· 2014-12-31
0.801
best: 0.906 (CAGFace)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
16konManga109 - 4x upscaling
PSNR· 2014-12-31
27.58
best: 33.19 (HMA†)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
16konManga109 - 4x upscaling
SSIM· 2014-12-31
0.8555
best: 0.9366 (Hi-IR-L)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
16konUrban100 - 4x upscaling
PSNR· 2014-12-31
24.52
best: 28.72 (Hi-IR-L)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
16konUrban100 - 4x upscaling
SSIM· 2014-12-31
0.7221
best: 0.9481 (SPSR)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
16konBSD100 - 4x upscaling
PSNR· 2014-12-31
26.9
best: 28.16 (DRCT-L)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
16konBSD100 - 4x upscaling
SSIM· 2014-12-31
0.7101
best: 0.851 (Edge-informed SR)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Anomaly DetectiononUCR Anomaly Archive
AUC ROC · 2024-11-01
0.5109
best: 0.8001 (SubLOF)
KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks arXiv:2411.00278

Graphs30 results

Super-ResolutiononSet5 - 4x upscaling
PSNR· 2014-12-31
30.49
best: 33.38 (HMA†)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononSet5 - 4x upscaling
SSIM· 2014-12-31
0.8628
best: 0.9103 (Hi-IR-L)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononSet14 - 4x upscaling
PSNR· 2014-12-31
27.5
best: 29.54 (DRCT-L)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononSet14 - 4x upscaling
SSIM· 2014-12-31
0.7513
best: 0.894 (Edge-informed SR)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
FID· 2014-12-31
147.21
best: 5.36 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
MS-SSIM· 2014-12-31
0.9
best: 0.971 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
PSNR· 2014-12-31
23.12
best: 28.65 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononFFHQ 256 x 256 - 4x upscaling
SSIM· 2014-12-31
0.688
best: 0.816 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononIXI
PSNR 2x T2w· 2014-12-31
37.32
best: 40.43 (EDSR+MMHCA)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononIXI
PSNR 4x T2w· 2014-12-31
29.69
best: 32.7 (EDSR+MMHCA)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononIXI
SSIM 4x T2w· 2014-12-31
0.9052
best: 0.9472 (SERAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononIXI
SSIM for 2x T2w· 2014-12-31
0.9796
best: 0.9877 (EDSR+MMHCA)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
FID· 2014-12-31
31.84
best: 1.978 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
MS-SSIM· 2014-12-31
0.924
best: 0.975 (HiFaceGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
PSNR· 2014-12-31
27.4
best: 34.1 (CAGFace)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononFFHQ 1024 x 1024 - 4x upscaling
SSIM· 2014-12-31
0.801
best: 0.906 (CAGFace)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononManga109 - 4x upscaling
PSNR· 2014-12-31
27.58
best: 33.19 (HMA†)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononManga109 - 4x upscaling
SSIM· 2014-12-31
0.8555
best: 0.9366 (Hi-IR-L)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononUrban100 - 4x upscaling
PSNR· 2014-12-31
24.52
best: 28.72 (Hi-IR-L)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononUrban100 - 4x upscaling
SSIM· 2014-12-31
0.7221
best: 0.9481 (SPSR)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononBSD100 - 4x upscaling
PSNR· 2014-12-31
26.9
best: 28.16 (DRCT-L)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononBSD100 - 4x upscaling
SSIM· 2014-12-31
0.7101
best: 0.851 (Edge-informed SR)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononMSU Video Upscalers: Quality Enhancement
PSNR· 2014-12-31
26.68
best: 31.28 (VEAI-AHQ-12)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononMSU Video Upscalers: Quality Enhancement
SSIM· 2014-12-31
0.929
best: 0.939 (iSeeBetter)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononMSU Video Upscalers: Quality Enhancement
VMAF· 2014-12-31
51.21
best: 61.2 (TecoGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononUltra Video Group HD - 4x upscaling
Average PSNR· 2014-12-31
37.52
best: 48.23 (RAMS (ours))
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononXiph HD - 4x upscaling
Average PSNR· 2014-12-31
31.47
best: 31.67 (ESPCN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononVid4 - 4x upscaling
MOVIE· 2014-12-31
6.9
best: 9.31 (bicubic)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononVid4 - 4x upscaling
PSNR· 2014-12-31
24.68
best: 31.36 (NeuriCam-net)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
Super-ResolutiononVid4 - 4x upscaling
SSIM· 2014-12-31
0.7158
best: 0.933 (NeuriCam-net)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092

Knowledge Base16 results

2D Human Pose EstimationonMSU Video Upscalers: Quality Enhancement
PSNR· 2014-12-31
26.68
best: 31.28 (VEAI-AHQ-12)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
2D Human Pose EstimationonMSU Video Upscalers: Quality Enhancement
SSIM· 2014-12-31
0.929
best: 0.939 (iSeeBetter)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
2D Human Pose EstimationonMSU Video Upscalers: Quality Enhancement
VMAF· 2014-12-31
51.21
best: 61.2 (TecoGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
2D Human Pose EstimationonUltra Video Group HD - 4x upscaling
Average PSNR· 2014-12-31
37.52
best: 48.23 (RAMS (ours))
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
2D Human Pose EstimationonXiph HD - 4x upscaling
Average PSNR· 2014-12-31
31.47
best: 31.67 (ESPCN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
2D Human Pose EstimationonVid4 - 4x upscaling
MOVIE· 2014-12-31
6.9
best: 9.31 (bicubic)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
2D Human Pose EstimationonVid4 - 4x upscaling
PSNR· 2014-12-31
24.68
best: 31.36 (NeuriCam-net)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
2D Human Pose EstimationonVid4 - 4x upscaling
SSIM· 2014-12-31
0.7158
best: 0.933 (NeuriCam-net)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Absolute Human Pose EstimationonMSU Video Upscalers: Quality Enhancement
PSNR· 2014-12-31
26.68
best: 31.28 (VEAI-AHQ-12)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Absolute Human Pose EstimationonMSU Video Upscalers: Quality Enhancement
SSIM· 2014-12-31
0.929
best: 0.939 (iSeeBetter)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Absolute Human Pose EstimationonMSU Video Upscalers: Quality Enhancement
VMAF· 2014-12-31
51.21
best: 61.2 (TecoGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Absolute Human Pose EstimationonUltra Video Group HD - 4x upscaling
Average PSNR· 2014-12-31
37.52
best: 48.23 (RAMS (ours))
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Absolute Human Pose EstimationonXiph HD - 4x upscaling
Average PSNR· 2014-12-31
31.47
best: 31.67 (ESPCN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Absolute Human Pose EstimationonVid4 - 4x upscaling
MOVIE· 2014-12-31
6.9
best: 9.31 (bicubic)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Absolute Human Pose EstimationonVid4 - 4x upscaling
PSNR· 2014-12-31
24.68
best: 31.36 (NeuriCam-net)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Absolute Human Pose EstimationonVid4 - 4x upscaling
SSIM· 2014-12-31
0.7158
best: 0.933 (NeuriCam-net)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092

Playing Games8 results

3D Face AnimationonMSU Video Upscalers: Quality Enhancement
PSNR· 2014-12-31
26.68
best: 31.28 (VEAI-AHQ-12)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Face AnimationonMSU Video Upscalers: Quality Enhancement
SSIM· 2014-12-31
0.929
best: 0.939 (iSeeBetter)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Face AnimationonMSU Video Upscalers: Quality Enhancement
VMAF· 2014-12-31
51.21
best: 61.2 (TecoGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Face AnimationonUltra Video Group HD - 4x upscaling
Average PSNR· 2014-12-31
37.52
best: 48.23 (RAMS (ours))
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Face AnimationonXiph HD - 4x upscaling
Average PSNR· 2014-12-31
31.47
best: 31.67 (ESPCN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Face AnimationonVid4 - 4x upscaling
MOVIE· 2014-12-31
6.9
best: 9.31 (bicubic)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Face AnimationonVid4 - 4x upscaling
PSNR· 2014-12-31
24.68
best: 31.36 (NeuriCam-net)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
3D Face AnimationonVid4 - 4x upscaling
SSIM· 2014-12-31
0.7158
best: 0.933 (NeuriCam-net)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092

Audio8 results

1 Image, 2*2 StitchionMSU Video Upscalers: Quality Enhancement
PSNR· 2014-12-31
26.68
best: 31.28 (VEAI-AHQ-12)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
1 Image, 2*2 StitchionMSU Video Upscalers: Quality Enhancement
SSIM· 2014-12-31
0.929
best: 0.939 (iSeeBetter)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
1 Image, 2*2 StitchionMSU Video Upscalers: Quality Enhancement
VMAF· 2014-12-31
51.21
best: 61.2 (TecoGAN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
1 Image, 2*2 StitchionUltra Video Group HD - 4x upscaling
Average PSNR· 2014-12-31
37.52
best: 48.23 (RAMS (ours))
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
1 Image, 2*2 StitchionXiph HD - 4x upscaling
Average PSNR· 2014-12-31
31.47
best: 31.67 (ESPCN)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
1 Image, 2*2 StitchionVid4 - 4x upscaling
MOVIE· 2014-12-31
6.9
best: 9.31 (bicubic)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
1 Image, 2*2 StitchionVid4 - 4x upscaling
PSNR· 2014-12-31
24.68
best: 31.36 (NeuriCam-net)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092
1 Image, 2*2 StitchionVid4 - 4x upscaling
SSIM· 2014-12-31
0.7158
best: 0.933 (NeuriCam-net)
SOTA
Image Super-Resolution Using Deep Convolutional Networks arXiv:1501.00092

Miscellaneous3 results

Fine-Grained Urban Flow InferenceonTaxiBJ-P1
MAE· 2019-02-06
2.491
best: 2.011 (UrbanFM)
SOTA
UrbanFM: Inferring Fine-Grained Urban Flows arXiv:1902.05377
Fine-Grained Urban Flow InferenceonTaxiBJ-P1
MSE· 2019-02-06
18.4642
best: 14.9232 (STCF)
SOTA
UrbanFM: Inferring Fine-Grained Urban Flows arXiv:1902.05377
Fine-Grained Urban Flow InferenceonTaxiBJ-P1
MAPE· 2019-02-06
0.714
best: 0.732 (ESPCN)
UrbanFM: Inferring Fine-Grained Urban Flows arXiv:1902.05377