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Found 3 papers, 1 papers with code
DAMSL: Domain Agnostic Meta Score-based Learning
In this paper, we propose Domain Agnostic Meta Score-based Learning (DAMSL), a novel, versatile and highly effective solution that delivers significant out-performance over state-of-the-art methods for cross-domain few-shot learning.
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Cross-Domain Few-Shot
on miniImagenet
SB-MTL: Score-based Meta Transfer-Learning for Cross-Domain Few-Shot Learning
Our method, called Score-based Meta Transfer-Learning (SB-MTL), combines transfer-learning and meta-learning by using a MAML-optimized feature encoder and a score-based Graph Neural Network.
Cross-Domain Few-Shot Learning with Meta Fine-Tuning
In our final results, we combine the novel method with the baseline method in a simple ensemble, and achieve an average accuracy of 73. 78% on the benchmark.
