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FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic Segmentation

11 Jun 2025arXiv:2506.11142archive 2025-07-28

Ebenezer Tarubinga, Jenifer Kalafatovich, Seong-Whan Lee

Semi-supervised semantic segmentation (SSSS) faces persistent challenges in effectively leveraging unlabeled data, such as ineffective utilization of pseudo-labels, exacerbation of class imbalance biases, and neglect of prediction uncertainty. Current approaches often discard uncertain regions through strict thresholding favouring dominant classes. To address these limitations, we introduce a holistic framework that transforms uncertainty into a learning asset through four principal components: (1) fuzzy pseudo-labeling, which preserves soft class distributions from top-K predictions to enrich supervision; (2) uncertainty-aware dynamic weighting, that modulate pixel-wise contributions via entropy-based reliability scores; (3) adaptive class rebalancing, which dynamically adjust losses to counteract long-tailed class distributions; and (4) lightweight contrastive regularization, that encourage compact and discriminative feature embeddings. Extensive experiments on benchmarks demonstrate that our method outperforms current state-of-the-art approaches, achieving significant improvements in the segmentation of under-represented classes and ambiguous regions.

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psychofict/FARCLUSS official report

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Tasks

Semantic SegmentationSemi-Supervised Semantic Segmentation

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Semi-Supervised Semantic Segmentation Cityscapes 12.5% labeled FARCLUSS Validation mIoU 78.5 #5 of 33 Archive leaderboard report
Semi-Supervised Semantic Segmentation Cityscapes 25% labeled FARCLUSS Validation mIoU 80.0 #4 of 30 Archive leaderboard report
Semi-Supervised Semantic Segmentation Cityscapes 50% labeled FARCLUSS Validation mIoU 81.0 #2 of 23 Archive leaderboard report
Semi-Supervised Semantic Segmentation Cityscapes 6.25% labeled FARCLUSS Validation mIoU 77.2 #5 of 18 Archive leaderboard report
Semi-Supervised Semantic Segmentation PASCAL VOC 2012 25% labeled FARCLUSS Validation mIoU 79.0 #11 of 27 Archive leaderboard report
Semi-Supervised Semantic Segmentation Pascal VOC 2012 12.5% labeled FARCLUSS Validation mIoU 78.2 #12 of 38 Archive leaderboard report
Semi-Supervised Semantic Segmentation Pascal VOC 2012 50% labeled FARCLUSS Validation mIoU 80.3 #2 of 3 Archive leaderboard report
Semi-Supervised Semantic Segmentation Pascal VOC 2012 6.25% labeled FARCLUSS Validation mIoU 76.4 #12 of 19 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

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