Alternatives and similar repositories for semantic-embeddings:

Users that are interested in semantic-embeddings are comparing it to the libraries listed below

• dichotomies / proxy-nca
  PyTorch Implementation of `No Fuss Distance Metric Learning using Proxies`.
  ☆181Updated 4 years ago
• wielandbrendel / bag-of-local-features-models
  Pretrained bag-of-local-features neural networks
  ☆312Updated 5 years ago
• CompVis / metric-learning-divide-and-conquer
  Source code for the paper "Divide and Conquer the Embedding Space for Metric Learning", CVPR 2019
  ☆264Updated 5 years ago
• 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"…
  ☆341Updated 2 years ago
• facebookresearch / DeeperCluster
  Implements the unsupervised pre-training of convolutional neural networks
  ☆250Updated 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
• macaodha / inat_comp_2018
  CNN training code for iNaturalist 2018 image classification competition
  ☆85Updated last year
• azgo14 / classification_metric_learning
  ☆102Updated 2 years ago
• facebookresearch / multigrain
  Code for "MultiGrain: a unified image embedding for classes and instances"
  ☆232Updated 5 years ago
• google / revisiting-self-supervised
  ☆352Updated 5 years ago
• kunhe / FastAP-metric-learning
  Code for CVPR 2019 paper "Deep Metric Learning to Rank"
  ☆96Updated 3 years ago
• idstcv / SoftTriple
  PyTorch Implementation for SoftTriple Loss
  ☆205Updated 9 months ago
• ducha-aiki / manifold-diffusion
  Diffusion on manifolds for image retrieval
  ☆126Updated 5 years ago
• facebookresearch / semi-supervised-ImageNet1K-models
  Semi-supervised ImageNet1K models
  ☆243Updated 5 years ago
• msight-tech / research-curriculumnet
  CurriculumNet: Weakly Supervised Learning from Large-Scale Web Images
  ☆158Updated 4 years ago
• facebookresearch / fair_self_supervision_benchmark
  Scaling and Benchmarking Self-Supervised Visual Representation Learning
  ☆586Updated 3 years ago
• KevinMusgrave / powerful-benchmarker
  A library for ML benchmarking. It's powerful.
  ☆438Updated last year
• google-research / remixmatch
  ☆129Updated 2 years ago
• fg91 / DeViSE-zero-shot-classification
  DeViSE model (zero-shot learning) trained on ImageNet and deployed on AWS using Docker
  ☆47Updated 6 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).
  ☆281Updated 9 months ago
• pierre-jacob / ICCV2019-Horde
  Code repository for our paper entilted "Metric Learning with HORDE: High-Order Regularizer for Deep Embeddings" accepted at ICCV 2019.
  ☆83Updated 2 years ago
• mangye16 / Unsupervised_Embedding_Learning
  Code for Unsupervised Embedding Learning via Invariant and Spreading Instance Feature
  ☆209Updated 5 years ago
• chaoyuaw / incubator-mxnet
  Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Juli…
  ☆114Updated 7 years ago
• ildoonet / unsupervised-data-augmentation
  Unofficial PyTorch Implementation of Unsupervised Data Augmentation.
  ☆146Updated 4 years ago
• noagarcia / keras_rmac
  RMAC implementation in Keras
  ☆84Updated 6 years ago
• XinshaoAmosWang / Ranked-List-Loss-for-DML
  CVPR 2019: Ranked List Loss for Deep Metric Learning, with extension for TPAMI submission
  ☆64Updated 4 years ago
• Confusezius / Deep-Metric-Learning-Baselines
  PyTorch Implementation for Deep Metric Learning Pipelines
  ☆572Updated 4 years ago
• kuanghuei / clean-net
  Tensorflow source code for "CleanNet: Transfer Learning for Scalable Image Classifier Training with Label Noise" (CVPR 2018)
  ☆88Updated 6 years ago
• vithursant / MagnetLoss-PyTorch
  PyTorch implementation of a deep metric learning technique called "Magnet Loss" from Facebook AI Research (FAIR) in ICLR 2016.
  ☆219Updated last year
• microsoft / snca.pytorch
  Improving Generalization via Scalable Neighborhood Component Analysis
  ☆137Updated last year