69 results for “topic:deep-metric-learning”
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
(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 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).
[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
Authors official Tensorflow implementation of the "Near-Duplicate Video Retrieval with Deep Metric Learning" [ICCVW 2017]
End-to-End Multi-Task Learning for Subject-Independent Motor Imagery EEG Classification (IEEE Transactions on Biomedical Engineering)
[ICCV 2021] Towards Interpretable Deep Metric Learning with Structural Matching
Code for CVPR 2019 paper "Deep Metric Learning to Rank"
A simple, modern and scalable facial recognition based attendance system built with Python back-end & Angular front-end.
PyTorch implementation of Deep Randomized Ensembles for Metric Learning(ECCV2018)
CVPR 2019: Ranked List Loss for Deep Metric Learning, with extension for TPAMI submission
Dogs classification with Deep Metric Learning
(CVPR 2020) This repo contains code for "PADS: Policy-Adapted Sampling for Visual Similarity Learning", which proposes learnable triplet mining with Reinforcement Learning.
(ICCV 2019) This repo contains code for "MIC: Mining Interclass Characteristics for Improved Metric Learning", which proposes an auxiliary training task to explain away intra-class variations.
Official PyTorch Implementation of ProxyGML Loss for Deep Metric Learning, NeurIPS 2020 (spotlight)
pytorch implement of this paper: https://arxiv.org/abs/1807.11176
(ICML 2021) Implementation for S2SD - Simultaneous Similarity-based Self-Distillation for Deep Metric Learning. Paper Link: https://arxiv.org/abs/2009.08348
Official PyTorch Implementation of Embedding Transfer with Label Relaxation for Improved Metric Learning, CVPR 2021
official pytorch implementation of "Deep Metric Learning with Spherical Embedding", NeurIPS 2020
Official PyTorch implementation of "Proxy Synthesis: Learning with Synthetic Classes for Deep Metric Learning" (AAAI 2021)
Minimalistic TensorFlow2+ deep metric/similarity learning library with loss functions, miners, and utils as embedding projector.
codes for TGRS paper: Graph Relation Network: Modeling Relations between Scenes for Multi-Label Remote Sensing Image Classification and Retrieval
(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.
Generalized Deep Metric Learning.
Metric Learning (npair loss & angular loss) on mnist and Visualizing by t_SNE
source code for the paper "Hard-Aware-Deeply-Cascaed-Embedding"