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Models/CNN-IL

CNN-IL

Reported on 16 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 Vision8 results

Image Super-ResolutiononIXI
PSNR 2x T2w· 2020-01-05
38.67
best: 40.43 (EDSR+MMHCA)
Convolutional Neural Networks with Intermediate Loss for 3D Super-Resolution of CT and MRI Scans arXiv:2001.01330
Image Super-ResolutiononIXI
PSNR 4x T2w· 2020-01-05
30.57
best: 32.7 (EDSR+MMHCA)
Convolutional Neural Networks with Intermediate Loss for 3D Super-Resolution of CT and MRI Scans arXiv:2001.01330
Image Super-ResolutiononIXI
SSIM 4x T2w· 2020-01-05
0.921
best: 0.9472 (SERAN)
Convolutional Neural Networks with Intermediate Loss for 3D Super-Resolution of CT and MRI Scans arXiv:2001.01330
Image Super-ResolutiononIXI
SSIM for 2x T2w· 2020-01-05
0.9837
best: 0.9877 (EDSR+MMHCA)
Convolutional Neural Networks with Intermediate Loss for 3D Super-Resolution of CT and MRI Scans arXiv:2001.01330
3D Object Super-ResolutiononIXI
PSNR 2x T2w· 2020-01-05
38.67
best: 40.43 (EDSR+MMHCA)
Convolutional Neural Networks with Intermediate Loss for 3D Super-Resolution of CT and MRI Scans arXiv:2001.01330
3D Object Super-ResolutiononIXI
PSNR 4x T2w· 2020-01-05
30.57
best: 32.7 (EDSR+MMHCA)
Convolutional Neural Networks with Intermediate Loss for 3D Super-Resolution of CT and MRI Scans arXiv:2001.01330
3D Object Super-ResolutiononIXI
SSIM 4x T2w· 2020-01-05
0.921
best: 0.9472 (SERAN)
Convolutional Neural Networks with Intermediate Loss for 3D Super-Resolution of CT and MRI Scans arXiv:2001.01330
3D Object Super-ResolutiononIXI
SSIM for 2x T2w· 2020-01-05
0.9837
best: 0.9877 (EDSR+MMHCA)
Convolutional Neural Networks with Intermediate Loss for 3D Super-Resolution of CT and MRI Scans arXiv:2001.01330

Graphs4 results

Super-ResolutiononIXI
PSNR 2x T2w· 2020-01-05
38.67
best: 40.43 (EDSR+MMHCA)
Convolutional Neural Networks with Intermediate Loss for 3D Super-Resolution of CT and MRI Scans arXiv:2001.01330
Super-ResolutiononIXI
PSNR 4x T2w· 2020-01-05
30.57
best: 32.7 (EDSR+MMHCA)
Convolutional Neural Networks with Intermediate Loss for 3D Super-Resolution of CT and MRI Scans arXiv:2001.01330
Super-ResolutiononIXI
SSIM 4x T2w· 2020-01-05
0.921
best: 0.9472 (SERAN)
Convolutional Neural Networks with Intermediate Loss for 3D Super-Resolution of CT and MRI Scans arXiv:2001.01330
Super-ResolutiononIXI
SSIM for 2x T2w· 2020-01-05
0.9837
best: 0.9877 (EDSR+MMHCA)
Convolutional Neural Networks with Intermediate Loss for 3D Super-Resolution of CT and MRI Scans arXiv:2001.01330

Methodology4 results

16konIXI
PSNR 2x T2w· 2020-01-05
38.67
best: 40.43 (EDSR+MMHCA)
Convolutional Neural Networks with Intermediate Loss for 3D Super-Resolution of CT and MRI Scans arXiv:2001.01330
16konIXI
PSNR 4x T2w· 2020-01-05
30.57
best: 32.7 (EDSR+MMHCA)
Convolutional Neural Networks with Intermediate Loss for 3D Super-Resolution of CT and MRI Scans arXiv:2001.01330
16konIXI
SSIM 4x T2w· 2020-01-05
0.921
best: 0.9472 (SERAN)
Convolutional Neural Networks with Intermediate Loss for 3D Super-Resolution of CT and MRI Scans arXiv:2001.01330
16konIXI
SSIM for 2x T2w· 2020-01-05
0.9837
best: 0.9877 (EDSR+MMHCA)
Convolutional Neural Networks with Intermediate Loss for 3D Super-Resolution of CT and MRI Scans arXiv:2001.01330