Generalizable Semantic Segmentation via Model-agnostic Learning and Target-specific Normalization

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Abstract:

Semantic segmentation methods in the supervised scenario have achieved significant improvement in recent years. However, when directly deploying the trained model to segment the images of unseen (or new coming) domains, its performance usually drops dramatically due to the data-distribution discrepancy between seen and unseen domains. T...More

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