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Found 2 papers, 1 papers with code
MetaSeg: Content-Aware Meta-Net for Omni-Supervised Semantic Segmentation
Noisy labels, inevitably existing in pseudo segmentation labels generated from weak object-level annotations, severely hampers model optimization for semantic segmentation.
Dynamic Loss For Robust Learning
Label noise and class imbalance commonly coexist in real-world data.
Ranked #6 on
Learning with noisy labels
on ANIMAL
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