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Segment objects by expanding high-quality regions with CorrMatch

Segment objects by expanding high-quality regions with CorrMatch


CorrMatch: Label Propagation via Correlation Matching for Semi-Supervised Semantic Segmentation

arXiv paper abstract https://arxiv.org/abs/2306.04300



... present a simple but performant semi-supervised semantic segmentation approach, termed CorrMatch.


... goal is to mine more high-quality regions from the unlabeled images to leverage the unlabeled data more efficiently via consistency regularization.


... introduce an adaptive threshold updating strategy with a relaxed initialization to expand the high-quality regions.


... propose to propagate high-confidence predictions through measuring the pairwise similarities between pixels.


... show that CorrMatch achieves great performance on popular semi-supervised semantic segmentation benchmarks.


... also achieve a consistent improvement over previous semi-supervised semantic segmentation models ...



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