most citedSemi-supervised Semantic Segmentation Meets Masked Modeling:Fine-grained Locality Learning Matters in Consistency Regularization

2 citations · 2 across the 1 of their papers we have counts for

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cs.CV2023★ 2 cited

Semi-supervised Semantic Segmentation Meets Masked Modeling:Fine-grained Locality Learning Matters in Consistency Regularization

Wentao Pan, Zhe Xu, Jiangpeng Yan +4

Semi-supervised semantic segmentation aims to utilize limited labeled images and abundant unlabeled images to achieve label-efficient learning, wherein the weak-to-strong consisten…