SANet

Reported on 36 benchmarks across 6 tasks · 1 paper

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

Computer Vision18 results

DehazingonSOTS Indoor
PSNR
40.4
best: 42.72 (ConvIR)
DehazingonSOTS Indoor
SSIM
0.996
best: 0.997 (ConvIR)
DehazingonSOTS Outdoor
PSNR
38.01
best: 40.73 (ChaIR)
DehazingonSOTS Outdoor
SSIM
0.995
best: 0.997 (ChaIR)
CrowdsonShanghaiTech B
MAE
8.4
best: 5.51 (EBC-ZIP-B)
CrowdsonShanghaiTech A
MAE
67
best: 47.81 (EBC-ZIP-B)
CrowdsonUCF CC 50
MAE
258.4
best: 154.8 (APGCC)
CrowdsonWorldExpo’10
Average MAE
8.2
best: 7.2 (ECAN)
Image DehazingonSOTS Indoor
PSNR
40.4
best: 42.72 (ConvIR)
Image DehazingonSOTS Indoor
SSIM
0.996
best: 0.997 (ConvIR)
Image DehazingonSOTS Outdoor
PSNR
38.01
best: 40.73 (ChaIR)
Image DehazingonSOTS Outdoor
SSIM
0.995
best: 0.997 (ChaIR)
Image SegmentationonMSD (Mirror Segmentation Dataset)
F-measure
0.877
best: 0.957 (SAM2-UNet)
Image SegmentationonMSD (Mirror Segmentation Dataset)
IoU
0.798
best: 0.918 (SAM2-UNet)
Image SegmentationonMSD (Mirror Segmentation Dataset)
MAE
0.054
best: 0.022 (SAM2-UNet)
Image SegmentationonPMD
F-measure
0.795
best: 0.826 (SAM2-UNet)
Image SegmentationonPMD
IoU
0.668
best: 0.728 (SAM2-UNet)
Image SegmentationonPMD
MAE
0.032
best: 0.027 (SAM2-UNet)

Medical12 results

Medical Image SegmentationonSUN-SEG-Easy (Unseen)
Dice· 2021-08-02
0.649
best: 0.9 (YOLO-SAM 2)
Shallow Attention Network for Polyp Segmentation arXiv:2108.00882
Medical Image SegmentationonSUN-SEG-Easy (Unseen)
S measure· 2021-08-02
0.72
best: 0.9 (YOLO-SAM 2)
Shallow Attention Network for Polyp Segmentation arXiv:2108.00882
Medical Image SegmentationonSUN-SEG-Easy (Unseen)
Sensitivity· 2021-08-02
0.521
best: 83.7 (YOLO-SAM 2)
Shallow Attention Network for Polyp Segmentation arXiv:2108.00882
Medical Image SegmentationonSUN-SEG-Easy (Unseen)
mean E-measure· 2021-08-02
0.745
best: 93.8 (YOLO-SAM 2)
Shallow Attention Network for Polyp Segmentation arXiv:2108.00882
Medical Image SegmentationonSUN-SEG-Easy (Unseen)
mean F-measure· 2021-08-02
0.634
best: 93.8 (YOLO-SAM 2)
Shallow Attention Network for Polyp Segmentation arXiv:2108.00882
Medical Image SegmentationonSUN-SEG-Easy (Unseen)
weighted F-measure· 2021-08-02
0.566
best: 0.794 (SALI)
Shallow Attention Network for Polyp Segmentation arXiv:2108.00882
Medical Image SegmentationonSUN-SEG-Hard (Unseen)
Dice· 2021-08-02
0.598
best: 0.902 (YOLO-SAM 2)
Shallow Attention Network for Polyp Segmentation arXiv:2108.00882
Medical Image SegmentationonSUN-SEG-Hard (Unseen)
S-Measure· 2021-08-02
0.706
best: 0.894 (YOLO-SAM 2)
Shallow Attention Network for Polyp Segmentation arXiv:2108.00882
Medical Image SegmentationonSUN-SEG-Hard (Unseen)
Sensitivity· 2021-08-02
0.505
best: 0.852 (YOLO-SAM 2)
Shallow Attention Network for Polyp Segmentation arXiv:2108.00882
Medical Image SegmentationonSUN-SEG-Hard (Unseen)
mean E-measure· 2021-08-02
0.743
best: 0.941 (YOLO-SAM 2)
Shallow Attention Network for Polyp Segmentation arXiv:2108.00882
Medical Image SegmentationonSUN-SEG-Hard (Unseen)
mean F-measure· 2021-08-02
0.58
best: 0.932 (YOLO-SAM 2)
Shallow Attention Network for Polyp Segmentation arXiv:2108.00882
Medical Image SegmentationonSUN-SEG-Hard (Unseen)
weighted F-measure· 2021-08-02
0.526
best: 0.79 (SALI)
Shallow Attention Network for Polyp Segmentation arXiv:2108.00882

Audio6 results

2D Semantic SegmentationonMSD (Mirror Segmentation Dataset)
F-measure
0.877
best: 0.957 (SAM2-UNet)
2D Semantic SegmentationonMSD (Mirror Segmentation Dataset)
IoU
0.798
best: 0.918 (SAM2-UNet)
2D Semantic SegmentationonMSD (Mirror Segmentation Dataset)
MAE
0.054
best: 0.022 (SAM2-UNet)
2D Semantic SegmentationonPMD
F-measure
0.795
best: 0.826 (SAM2-UNet)
2D Semantic SegmentationonPMD
IoU
0.668
best: 0.728 (SAM2-UNet)
2D Semantic SegmentationonPMD
MAE
0.032
best: 0.027 (SAM2-UNet)