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Models/FARCLUSS

FARCLUSS

Reported on 16 benchmarks across 2 tasks · 1 paper · 6 SOTA

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

Medical8 results

Semantic SegmentationonCityscapes 50% labeled
Validation mIoU· 2025-06-11
81
SOTA
FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic Segmentation arXiv:2506.11142
Semantic SegmentationonCityscapes 12.5% labeled
Validation mIoU· 2025-06-11
78.5
SOTA
FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic Segmentation arXiv:2506.11142
Semantic SegmentationonCityscapes 25% labeled
Validation mIoU· 2025-06-11
80
SOTA
FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic Segmentation arXiv:2506.11142
Semantic SegmentationonPascal VOC 2012 50% labeled
Validation mIoU· 2025-06-11
80.3
best: 81.13 (AllSpark)
FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic Segmentation arXiv:2506.11142
Semantic SegmentationonPascal VOC 2012 6.25% labeled
Validation mIoU· 2025-06-11
76.4
best: 82 (SemiOVS (w/ PrevMatch, ResNet-101))
FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic Segmentation arXiv:2506.11142
Semantic SegmentationonPASCAL VOC 2012 25% labeled
Validation mIoU· 2025-06-11
79
best: 81.3 (SemiOVS (w/ PrevMatch, ResNet-101))
FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic Segmentation arXiv:2506.11142
Semantic SegmentationonPascal VOC 2012 12.5% labeled
Validation mIoU· 2025-06-11
78.2
best: 82.4 (SemiOVS (w/ UniMatch, ResNet-101))
FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic Segmentation arXiv:2506.11142
Semantic SegmentationonCityscapes 6.25% labeled
Validation mIoU· 2025-06-11
77.2
best: 83.6 (UniMatch V2 (DINOv2-B))
FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic Segmentation arXiv:2506.11142

Audio8 results

10-shot image generationonCityscapes 50% labeled
Validation mIoU· 2025-06-11
81
SOTA
FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic Segmentation arXiv:2506.11142
10-shot image generationonCityscapes 12.5% labeled
Validation mIoU· 2025-06-11
78.5
SOTA
FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic Segmentation arXiv:2506.11142
10-shot image generationonCityscapes 25% labeled
Validation mIoU· 2025-06-11
80
SOTA
FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic Segmentation arXiv:2506.11142
10-shot image generationonPascal VOC 2012 50% labeled
Validation mIoU· 2025-06-11
80.3
best: 81.13 (AllSpark)
FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic Segmentation arXiv:2506.11142
10-shot image generationonPascal VOC 2012 6.25% labeled
Validation mIoU· 2025-06-11
76.4
best: 82 (SemiOVS (w/ PrevMatch, ResNet-101))
FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic Segmentation arXiv:2506.11142
10-shot image generationonPASCAL VOC 2012 25% labeled
Validation mIoU· 2025-06-11
79
best: 81.3 (SemiOVS (w/ PrevMatch, ResNet-101))
FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic Segmentation arXiv:2506.11142
10-shot image generationonPascal VOC 2012 12.5% labeled
Validation mIoU· 2025-06-11
78.2
best: 82.4 (SemiOVS (w/ UniMatch, ResNet-101))
FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic Segmentation arXiv:2506.11142
10-shot image generationonCityscapes 6.25% labeled
Validation mIoU· 2025-06-11
77.2
best: 83.6 (UniMatch V2 (DINOv2-B))
FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic Segmentation arXiv:2506.11142