Alternatives and similar repositories for OnlineMiningTripletLoss

Users that are interested in OnlineMiningTripletLoss are comparing it to the libraries listed below

• cvqluu / Angular-Penalty-Softmax-Losses-Pytorch
  Angular penalty loss functions in Pytorch (ArcFace, SphereFace, Additive Margin, CosFace)
  ☆491Updated last year
• Confusezius / Revisiting_Deep_Metric_Learning_PyTorch
  (ICML 2020) This repo contains code for our paper "Revisiting Training Strategies and Generalization Performance in Deep Metric Learning"…
  ☆343Updated 3 years ago
• dichotomies / proxy-nca
  PyTorch Implementation of `No Fuss Distance Metric Learning using Proxies`.
  ☆182Updated 5 years ago
• YirongMao / softmax_variants
  PyTorch code for softmax variants: center loss, cosface loss, large-margin gaussian mixture, COCOLoss, ring loss
  ☆255Updated 7 years ago
• CompVis / metric-learning-divide-and-conquer
  Source code for the paper "Divide and Conquer the Embedding Space for Metric Learning", CVPR 2019
  ☆265Updated 5 years ago
• azgo14 / classification_metric_learning
  ☆102Updated 2 years ago
• facebookresearch / DeeperCluster
  Implements the unsupervised pre-training of convolutional neural networks
  ☆252Updated 3 years ago
• jeromerony / dml_cross_entropy
  Code for the paper "A unifying mutual information view of metric learning: cross-entropy vs. pairwise losses" (ECCV 2020 - Spotlight)
  ☆168Updated 2 years ago
• amirhfarzaneh / lsoftmax-pytorch
  The Pytorch Implementation of L-Softmax
  ☆188Updated 6 years ago
• sung-yeon-kim / Proxy-Anchor-CVPR2020
  Official PyTorch Implementation of Proxy Anchor Loss for Deep Metric Learning, CVPR 2020
  ☆321Updated 3 years ago
• cvjena / semantic-embeddings
  Hierarchy-based Image Embeddings for Semantic Image Retrieval
  ☆267Updated 4 years ago
• msight-tech / research-ms-loss
  MS-Loss: Multi-Similarity Loss for Deep Metric Learning
  ☆499Updated 2 years ago
• idstcv / SoftTriple
  PyTorch Implementation for SoftTriple Loss
  ☆208Updated last year
• 4uiiurz1 / pytorch-adacos
  PyTorch implementation of AdaCos
  ☆212Updated 4 years ago
• ecs-vlc / FMix
  Official implementation of 'FMix: Enhancing Mixed Sample Data Augmentation'
  ☆338Updated 4 years ago
• Confusezius / Deep-Metric-Learning-Baselines
  PyTorch Implementation for Deep Metric Learning Pipelines
  ☆574Updated 5 years ago
• mangye16 / Unsupervised_Embedding_Learning
  Code for Unsupervised Embedding Learning via Invariant and Spreading Instance Feature
  ☆210Updated 6 years ago
• alfonmedela / triplet-loss-pytorch
  Highly efficient PyTorch version of the Semi-hard Triplet loss ⚡️
  ☆116Updated 3 years ago
• KevinMusgrave / powerful-benchmarker
  A library for ML benchmarking. It's powerful.
  ☆439Updated last year
• msight-tech / research-xbm
  XBM: Cross-Batch Memory for Embedding Learning
  ☆310Updated 2 years ago
• richardaecn / class-balanced-loss
  Class-Balanced Loss Based on Effective Number of Samples. CVPR 2019
  ☆612Updated 3 years ago
• uoguelph-mlrg / confidence_estimation
  Learning Confidence for Out-of-Distribution Detection in Neural Networks
  ☆275Updated 7 years ago
• mpyrozhok / adamwr
  Implements https://arxiv.org/abs/1711.05101 AdamW optimizer, cosine learning rate scheduler and "Cyclical Learning Rates for Training Neu…
  ☆150Updated 6 years ago
• google-research / noisystudent
  Code for Noisy Student Training. https://arxiv.org/abs/1911.04252
  ☆764Updated 4 years ago
• imbue-ai / self_supervised
  A Pytorch-Lightning implementation of self-supervised algorithms
  ☆542Updated 3 years ago
• andreasveit / triplet-network-pytorch
  ☆377Updated 6 years ago
• karanchahal / distiller
  A large scale study of Knowledge Distillation.
  ☆220Updated 5 years ago
• ildoonet / unsupervised-data-augmentation
  Unofficial PyTorch Implementation of Unsupervised Data Augmentation.
  ☆147Updated 4 years ago
• leeesangwon / PyTorch-Image-Retrieval
  A PyTorch framework for an image retrieval task including implementation of N-pair Loss (NIPS 2016) and Angular Loss (ICCV 2017).
  ☆282Updated last year
• yukimasano / self-label
  Self-labelling via simultaneous clustering and representation learning. (ICLR 2020)
  ☆541Updated last year