216 Open source projects that are alternatives of or similar to awesome-few-shot-meta-learning

FSL-Mate: A collection of resources for few-shot learning (FSL).

Awesome Few-shot learning

Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning

Tensorflow implementation for paper: Learning to Compare: Relation Network for Few-Shot Learning.

Source codes for "Improved Few-Shot Visual Classification" (CVPR 2020), "Enhancing Few-Shot Image Classification with Unlabelled Examples" (WACV 2022), and "Beyond Simple Meta-Learning: Multi-Purpose Models for Multi-Domain, Active and Continual Few-Shot Learning" (Neural Networks 2022 - in submission)

Code of Empirical Bayes Transductive Meta-Learning with Synthetic Gradients

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

Finetuning any DNN for better embedding on neural search tasks

Learning To Compare For Text , Few shot learning in text classification

[IJCAI 2021] Cross-Domain Few-Shot Classification via Adversarial Task Augmentation

Hierarchical Co-occurrence Network with Prototype Loss for Few-shot Learning (PyTorch)

Official PyTorch implementation of "Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning" (ICCV2021 Oral)

PyTorch code for NeurIPSW 2020 paper (4th Workshop on Meta-Learning) "Few-Shot Unsupervised Continual Learning through Meta-Examples"

LibFewShot: A Comprehensive Library for Few-shot Learning.

One-Shot Recognition of Manufacturing Defects in Steel Surfaces

Official repository of https://arxiv.org/abs/2111.04040v1

One-Shot Learning with Triplet CNNs in Pytorch

Tensorflow Implementation of FaceNet: A Unified Embedding for Face Recognition and Clustering to find the celebrity whose face matches the closest to yours.

Metric learning algorithms in Python

finetune bert for small dataset text classification in a few-shot learning manner using ProtoNet

The first fully convolutional metric learning for geometric/semantic image correspondences.

https://www.kaggle.com/c/humpback-whale-identification

A simple LaTeX template for Technical Reports, arXiv preprints & 2-column Conference papers

Source code for the paper "Divide and Conquer the Embedding Space for Metric Learning", CVPR 2019

A simple yet effective loss function for face verification.

A comprehensive survey of deep metric learning and related works

Open source person re-identification library in python

Implementation of our paper "Meta Reinforcement Learning with Task Embedding and Shared Policy"

Official PyTorch implementation of "Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets" (ICLR 2021)

PyTorch implementation of a deep metric learning technique called "Magnet Loss" from Facebook AI Research (FAIR) in ICLR 2016.

In defence of metric learning for speaker recognition

Code for the NeurIPS 2017 Paper "Prototypical Networks for Few-shot Learning"

Angular penalty loss functions in Pytorch (ArcFace, SphereFace, Additive Margin, CosFace)

This is the implementation of paper <Additive Margin Softmax for Face Verification>

PyTorch code for BMVC 2018 paper: "Self-Paced Learning with Adaptive Visual Embeddings"

PyTorch Implementation for Deep Metric Learning Pipelines

Accelerated deep learning R&D

Hardnet descriptor model - "Working hard to know your neighbor's margins: Local descriptor learning loss"

A PyTorch framework for an image retrieval task including implementation of N-pair Loss (NIPS 2016) and Angular Loss (ICCV 2017).

Official source code of "Batch DropBlock Network for Person Re-identification and Beyond" (ICCV 2019)

The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

A PyTorch library for benchmarking deep metric learning. It's powerful.

A novel method to tune language models. Codes and datasets for paper ``GPT understands, too''.

Improved Deep Metric Learning with Multi-class N-pair Loss Objective

Knowledge-Aware machine LEarning (KALE): accessible machine learning from multiple sources for interdisciplinary research, part of the 🔥PyTorch ecosystem

(ICML 2020) This repo contains code for our paper "Revisiting Training Strategies and Generalization Performance in Deep Metric Learning" (https://arxiv.org/abs/2002.08473) to facilitate consistent research in the field of Deep Metric Learning.

Official pytorch Implementation of Relational Knowledge Distillation, CVPR 2019

Pytorch ReID: A tiny, friendly, strong pytorch implement of object re-identification baseline. Tutorial 👉https://github.com/layumi/Person_reID_baseline_pytorch/tree/master/tutorial

Deep metric learning methods implemented in Chainer

Official Tensorflow implementation of "Symmetrical Synthesis for Deep Metric Learning" (AAAI 2020)

🧶 Modular VAE disentanglement framework for python built with PyTorch Lightning ▸ Including metrics and datasets ▸ With strongly supervised, weakly supervised and unsupervised methods ▸ Easily configured and run with Hydra config ▸ Inspired by disentanglement_lib

TensorFlow 2.0 implementation of MAML.

SegSort: Segmentation by Discriminative Sorting of Segments

Adversarial Ranking Attack and Defense, ECCV, 2020.

Code for the paper "A unifying mutual information view of metric learning: cross-entropy vs. pairwise losses" (ECCV 2020 - Spotlight)

Playground of Metric Learning with MNIST @pytorch. We provide ArcFace, CosFace, SphereFace, CircleLoss and visualization.

PyTorch implementation of 'Squeeze and Excite' Guided Few Shot Segmentation of Volumetric Scans

Project page for Heated-up Softmax Embedding

The corresponding code from our paper "DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations". Do not hesitate to open an issue if you run into any trouble!

R package for Distance Metric Learning