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Task-Adaptive Feature Transformer with Semantic Enrichment for Few-Shot Segmentation
The task-conditioned feature transformation allows an effective utilization of the semantic information in novel classes to generate tight segmentation masks.
Task-Adaptive Feature Transformer for Few-Shot Segmentation
Few-shot learning allows machines to classify novel classes using only a few labeled samples.
CAFENet: Class-Agnostic Few-Shot Edge Detection Network
Since there is no existing dataset for few-shot semantic edge detection, we construct two new datasets, FSE-1000 and SBD-$5^i$, and evaluate the performance of the proposed CAFENet on them.
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