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Found 2 papers, 1 papers with code
Weakly-Supervised Domain Adaptive Semantic Segmentation With Prototypical Contrastive Learning
In this work, we propose a common framework to use different weak labels, e. g. image, point and coarse labels from target domain to reduce this performance gap.
Urban Scene Semantic Segmentation with Low-Cost Coarse Annotation
For best performance, today's semantic segmentation methods use large and carefully labeled datasets, requiring expensive annotation budgets.
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