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02/14/2022
Task-Adaptive Feature Transformer with Semantic Enrichment for Few-Shot Segmentation
Few-shot learning allows machines to classify novel classes using only a...
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10/22/2020
Task-Adaptive Feature Transformer for Few-Shot Segmentation
Few-shot learning allows machines to classify novel classes using only a...
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03/19/2020
XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning
Learning novel concepts while preserving prior knowledge is a long-stand...
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03/18/2020
CAFENet: Class-Agnostic Few-Shot Edge Detection Network
We tackle a novel few-shot learning challenge, which we call few-shot se...
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03/18/2020
Task-Adaptive Clustering for Semi-Supervised Few-Shot Classification
Few-shot learning aims to handle previously unseen tasks using only a sm...
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05/16/2019
TapNet: Neural Network Augmented with Task-Adaptive Projection for Few-Shot Learning
Handling previously unseen tasks after given only a few training example...
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06/04/2018
