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Models/U2PL (DeepLab v3+ with ResNet-101)

U2PL (DeepLab v3+ with ResNet-101)

Reported on 10 benchmarks across 2 tasks · 1 paper · 8 SOTA

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

Medical5 results

Semantic SegmentationonPASCAL VOC 2012 92 labeled
Validation mIoU· 2022-03-08
68
best: 87 (SemiOVS (w/ SemiVL, ViT-B/16))
SOTA
Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels arXiv:2203.03884
Semantic SegmentationonPASCAL VOC 2012 732 labeled
Validation mIoU· 2022-03-08
76.2
best: 90 (UniMatch V2 (DINOv2-B))
SOTA
Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels arXiv:2203.03884
Semantic SegmentationonPASCAL VOC 2012 366 labeled
Validation mIoU· 2022-03-08
73.7
best: 88.9 (UniMatch V2 (DINOv2-B))
SOTA
Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels arXiv:2203.03884
Semantic SegmentationonPASCAL VOC 2012 183 labeled
Validation mIoU· 2022-03-08
69.2
best: 87.9 (UniMatch V2 (DINOv2-B))
SOTA
Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels arXiv:2203.03884
Semantic SegmentationonPASCAL VOC 2012 1464 labels
Validation mIoU· 2022-03-08
79.5
best: 90.8 (UniMatch V2 (DINOv2-B))
Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels arXiv:2203.03884

Audio5 results

10-shot image generationonPASCAL VOC 2012 92 labeled
Validation mIoU· 2022-03-08
68
best: 87 (SemiOVS (w/ SemiVL, ViT-B/16))
SOTA
Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels arXiv:2203.03884
10-shot image generationonPASCAL VOC 2012 732 labeled
Validation mIoU· 2022-03-08
76.2
best: 90 (UniMatch V2 (DINOv2-B))
SOTA
Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels arXiv:2203.03884
10-shot image generationonPASCAL VOC 2012 366 labeled
Validation mIoU· 2022-03-08
73.7
best: 88.9 (UniMatch V2 (DINOv2-B))
SOTA
Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels arXiv:2203.03884
10-shot image generationonPASCAL VOC 2012 183 labeled
Validation mIoU· 2022-03-08
69.2
best: 87.9 (UniMatch V2 (DINOv2-B))
SOTA
Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels arXiv:2203.03884
10-shot image generationonPASCAL VOC 2012 1464 labels
Validation mIoU· 2022-03-08
79.5
best: 90.8 (UniMatch V2 (DINOv2-B))
Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels arXiv:2203.03884