There are 23 repositories under metric-learning topic.
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
Torchreid: Deep learning person re-identification in PyTorch.
:bouncing_ball_person: Pytorch ReID: A tiny, friendly, strong pytorch implement of person re-id / vehicle re-id baseline. Tutorial 👉https://github.com/layumi/Person_reID_baseline_pytorch/tree/master/tutorial
Accelerated deep learning R&D
Metric learning algorithms in Python
Code for the NeurIPS 2017 Paper "Prototypical Networks for Few-shot Learning"
In defence of metric learning for speaker recognition
TensorFlow Similarity is a python package focused on making similarity learning quick and easy.
Metric learning and retrieval pipelines, models and zoo.
https://www.kaggle.com/c/humpback-whale-identification
PyTorch Implementation for Deep Metric Learning Pipelines
Paper List for Contrastive Learning for Natural Language Processing
Hardnet descriptor model - "Working hard to know your neighbor's margins: Local descriptor learning loss"
😎 A curated list of awesome practical Metric Learning and its applications
Angular penalty loss functions in Pytorch (ArcFace, SphereFace, Additive Margin, CosFace)
This is the implementation of paper <Additive Margin Softmax for Face Verification>
A library for ML benchmarking. It's powerful.
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!
(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 source code of "Batch DropBlock Network for Person Re-identification and Beyond" (ICCV 2019)
A PyTorch framework for an image retrieval task including implementation of N-pair Loss (NIPS 2016) and Angular Loss (ICCV 2017).
Source code for the paper "Divide and Conquer the Embedding Space for Metric Learning", CVPR 2019
PyTorch implementation of a deep metric learning technique called "Magnet Loss" from Facebook AI Research (FAIR) in ICLR 2016.
[ECCV 2020] QAConv: Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting, and [CVPR 2022] GS: Graph Sampling Based Deep Metric Learning
[NAACL'21 & ACL'21] SapBERT: Self-alignment pretraining for BERT & XL-BEL: Cross-Lingual Biomedical Entity Linking.
Code for the paper "A unifying mutual information view of metric learning: cross-entropy vs. pairwise losses" (ECCV 2020 - Spotlight)
DeeplyTough: Learning Structural Comparison of Protein Binding Sites
Deep metric learning methods implemented in Chainer
SegSort: Segmentation by Discriminative Sorting of Segments
Deep Face Recognition in PyTorch