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Models/FreDSNet

FreDSNet

Reported on 6 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 Vision2 results

Depth EstimationonStanford2D3D Panoramic
RMSE· 2022-10-04
0.2727
best: 0.2619 (HiMODE)
FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier Convolutions arXiv:2210.01595
Depth EstimationonStanford2D3D Panoramic
absolute relative error· 2022-10-04
0.0952
best: 0.0405 (PanoFormer)
FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier Convolutions arXiv:2210.01595

Methodology2 results

3DonStanford2D3D Panoramic
RMSE· 2022-10-04
0.2727
best: 0.2619 (HiMODE)
FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier Convolutions arXiv:2210.01595
3DonStanford2D3D Panoramic
absolute relative error· 2022-10-04
0.0952
best: 0.0405 (PanoFormer)
FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier Convolutions arXiv:2210.01595

Medical1 result

Semantic SegmentationonStanford2D3D Panoramic
mAcc· 2022-10-04
63.1
best: 70.68 (SFSS-MMSI (RGB+HHA))
FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier Convolutions arXiv:2210.01595

Audio1 result

10-shot image generationonStanford2D3D Panoramic
mAcc· 2022-10-04
63.1
best: 70.68 (SFSS-MMSI (RGB+HHA))
FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier Convolutions arXiv:2210.01595