Repository for few-shot learning machine learning projects

Tools for generating mini-ImageNet dataset and processing batches

Leaderboards for few-shot image classification on miniImageNet, tieredImageNet, FC100, and CIFAR-FS.

This repo provides pytorch code which replicates the results of the Matching Networks for One Shot Learning paper on the Omniglot and MiniImageNet dataset

Tensorflow implementation of NIPS 2017 Paper "Prototypical Networks for Few-shot Learning"

A lightweight library that implements state-of-the-art few-shot learning algorithms.

This repository contains the code for the paper: Cooperative Bi-path Metric for Few-shot Learning, Zeyuan Wang, Yifan Zhao, Jia Li, Yonghong Tian, ACM Conference on Multimedia (ACM MM), 2020

The source code for Multi-Scale Kronecker-Product Relation Networks for Few-Shot Learning

MAML implementation in PyTorch.

Official implementation of the paper: Learn to aggregate global and local representations for few-shot learning

Very simple MAML-like metalearning baseline

This repo provides pytorch code which replicates the results of the Matching Networks for One Shot Learning paper on the Omniglot and MiniImageNet dataset