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Found 3 papers, 2 papers with code
Shallow Bayesian Meta Learning for Real-World Few-Shot Recognition
Current state-of-the-art few-shot learners focus on developing effective training procedures for feature representations, before using simple, e. g. nearest centroid, classifiers.
Ranked #6 on
Few-Shot Image Classification
on Meta-Dataset
cross-domain few-shot learning
Few-Shot Image Classification
Tensor Composition Net for Visual Relationship Prediction
We present a novel Tensor Composition Net (TCN) to predict visual relationships in images.
RelationNet2: Deep Comparison Columns for Few-Shot Learning
We thus propose a new deep comparison network comprised of embedding and relation modules that learn multiple non-linear distance metrics based on different levels of features simultaneously.
