205 Open source projects that are alternatives of or similar to Awesome-Few-shot

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)

awesome few shot / meta learning papers

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

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

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

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

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

Meta-DETR: Official PyTorch Implementation

Finetuning any DNN for better embedding on neural search tasks

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

(ECCV 2020) PyTorch implementation of paper "Few-Shot Object Detection and Viewpoint Estimation for Objects in the Wild"

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

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

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

Code of Empirical Bayes Transductive Meta-Learning with Synthetic Gradients

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

LibFewShot: A Comprehensive Library for Few-shot Learning.

In defence of metric learning for speaker recognition

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!

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

Official pytorch Implementation of Relational Knowledge Distillation, CVPR 2019

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

Polysemous Visual-Semantic Embedding for Cross-Modal Retrieval (CVPR 2019)

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

Adversarial Ranking Attack and Defense, ECCV, 2020.

Multi-View Graph Convolutional Network and Its Applications on Neuroimage Analysis for Parkinson's Disease (AMIA 2018)

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

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

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

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

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

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

PyTorch implementation of “Negative Margin Matters: Understanding Margin in Few-shot Classification”

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

Code for ACL'19 "Few-Shot Representation Learning for Out-Of-Vocabulary Words"

🧶 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

Global-Local Bidirectional Reasoning for Unsupervised Representation Learning of 3D Point Clouds (CVPR 2020)

Accelerated deep learning R&D

Open source person re-identification library in python

Project page for Heated-up Softmax Embedding

R package for Distance Metric Learning

ePillID Dataset: A Low-Shot Fine-Grained Benchmark for Pill Identification (CVPR 2020 VL3)

TensorFlow 2.0 implementation of MAML.

📄 Spatial Contrastive Learning for Few-Shot Classification (ECML/PKDD 2021).

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

Metric learning algorithms in Python

MinkLoc3D: Point Cloud Based Large-Scale Place Recognition

Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning

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

Retrieve recipes from foodie pictures using Deep Learning and Pytorch

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

scLearn：Learning for single cell assignment

Code for NeurIPS 2019 Paper

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

Local Fisher Discriminant Analysis in R

Deep Metric and Hash Code Learning Network for Content Based Retrieval of Remote Sensing Images

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

(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.

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

Papers and Codes about Deep Metric Learning/Deep Embedding