The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
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Updated
Apr 1, 2024 - Python
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
Deep Metric Learning
PyTorch Implementation for Deep Metric Learning Pipelines
Official PyTorch Implementation of Proxy Anchor Loss for Deep Metric Learning, CVPR 2020
A PyTorch framework for an image retrieval task including implementation of N-pair Loss (NIPS 2016) and Angular Loss (ICCV 2017).
(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.
[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
图像检索和向量搜索,similarity learning,compare deep metric and deep-hashing applying in image retrieval
A simple, modern and scalable facial recognition based attendance system built with Python back-end & Angular front-end.
End-to-End Multi-Task Learning for Subject-Independent Motor Imagery EEG Classification (IEEE Transactions on Biomedical Engineering)
Authors official Tensorflow implementation of the "Near-Duplicate Video Retrieval with Deep Metric Learning" [ICCVW 2017]
Code for CVPR 2019 paper "Deep Metric Learning to Rank"
PyTorch implementation of Deep Randomized Ensembles for Metric Learning(ECCV2018)
source code for the paper "Hard-Aware-Deeply-Cascaed-Embedding"
(ECCV 2020) This repo contains code for "DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning" (https://arxiv.org/abs/2004.13458), which extends vanilla DML with auxiliary and self-supervised features.
Dogs classification with Deep Metric Learning
pytorch implement of this paper: https://arxiv.org/abs/1807.11176
(CVPR 2020) This repo contains code for "PADS: Policy-Adapted Sampling for Visual Similarity Learning", which proposes learnable triplet mining with Reinforcement Learning.
[ICCV 2021] Towards Interpretable Deep Metric Learning with Structural Matching
Official PyTorch Implementation of ProxyGML Loss for Deep Metric Learning, NeurIPS 2020 (spotlight)
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