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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
This is the implementation of paper <Additive Margin Softmax for Face Verification>
A simple yet effective loss function for face verification.
Angular penalty loss functions in Pytorch (ArcFace, SphereFace, Additive Margin, CosFace)