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Models/AMN (DeepLabV2-ResNet101)

AMN (DeepLabV2-ResNet101)

Reported on 6 benchmarks across 2 tasks · 1 paper · 2 SOTA

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

Medical3 results

Semantic SegmentationonCOCO 2014 val
mIoU· 2022-03-30
44.7
best: 56.8 (DHR (Swin-L, Mask2Former))
SOTA
Threshold Matters in WSSS: Manipulating the Activation for the Robust and Accurate Segmentation Model Against Thresholds arXiv:2203.16045
Semantic SegmentationonPASCAL VOC 2012 val
Mean IoU· 2022-03-30
69.5
best: 83.4 (SemPLeS (Swin-L))
Threshold Matters in WSSS: Manipulating the Activation for the Robust and Accurate Segmentation Model Against Thresholds arXiv:2203.16045
Semantic SegmentationonPASCAL VOC 2012 test
Mean IoU· 2022-03-30
69.6
best: 82.9 (SemPLeS (Swin-L))
Threshold Matters in WSSS: Manipulating the Activation for the Robust and Accurate Segmentation Model Against Thresholds arXiv:2203.16045

Audio3 results

10-shot image generationonCOCO 2014 val
mIoU· 2022-03-30
44.7
best: 56.8 (DHR (Swin-L, Mask2Former))
SOTA
Threshold Matters in WSSS: Manipulating the Activation for the Robust and Accurate Segmentation Model Against Thresholds arXiv:2203.16045
10-shot image generationonPASCAL VOC 2012 val
Mean IoU· 2022-03-30
69.5
best: 83.4 (SemPLeS (Swin-L))
Threshold Matters in WSSS: Manipulating the Activation for the Robust and Accurate Segmentation Model Against Thresholds arXiv:2203.16045
10-shot image generationonPASCAL VOC 2012 test
Mean IoU· 2022-03-30
69.6
best: 82.9 (SemPLeS (Swin-L))
Threshold Matters in WSSS: Manipulating the Activation for the Robust and Accurate Segmentation Model Against Thresholds arXiv:2203.16045