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.

⛹️ 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

🎯 Task-oriented embedding tuning for BERT, CLIP, etc.

Metric learning algorithms in Python

Open source person re-identification library 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.

Blazing fast framework for fine-tuning similarity learning models

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 simple yet effective loss function for face verification.