kaidic / LDAM-DRWLinks
[NeurIPS 2019] Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
☆673Updated 3 years ago
Alternatives and similar repositories for LDAM-DRW
Users that are interested in LDAM-DRW are comparing it to the libraries listed below
Sorting:
- This repository contains code for the paper "Decoupling Representation and Classifier for Long-Tailed Recognition", published at ICLR 202…☆971Updated 3 years ago
- A curated list of long-tailed recognition resources.☆584Updated last year
- Code for paper: DivideMix: Learning with Noisy Labels as Semi-supervised Learning☆556Updated 4 years ago
- [NeurIPS 2020] This project provides a strong single-stage baseline for Long-Tailed Classification, Detection, and Instance Segmentation …☆568Updated 9 months ago
- The official PyTorch implementation of paper BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition☆669Updated 2 years ago
- Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"☆798Updated last year
- Code for "MixMatch - A Holistic Approach to Semi-Supervised Learning"☆648Updated last year
- Class-Balanced Loss Based on Effective Number of Samples. CVPR 2019☆611Updated 3 years ago
- PseudoLabel 2013, VAT, PI model, Tempens, MeanTeacher, ICT, MixMatch, FixMatch☆451Updated 2 years ago
- Pytorch implementation for "Large-Scale Long-Tailed Recognition in an Open World" (CVPR 2019 ORAL)☆863Updated 2 years ago
- [NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning☆752Updated 4 years ago
- NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels☆506Updated 3 years ago
- [ICLR 2021 Spotlight] Code release for "Long-tailed Recognition by Routing Diverse Distribution-Aware Experts."☆271Updated 2 years ago
- Unofficial PyTorch implementation of "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence"☆785Updated 2 years ago
- PyTorch code for "Prototypical Contrastive Learning of Unsupervised Representations"☆590Updated last month
- [ ECCV 2020 Spotlight ] Pytorch implementation for "Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets"☆368Updated 2 years ago
- NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).☆288Updated 3 years ago
- Reproduce Results for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels" https://arxiv.org/abs/1908.06112☆186Updated 4 years ago
- This repo consists of collection of papers and repos on the topic of deep learning by noisy labels / label noise.☆233Updated 3 years ago
- Official Implementation of ICML 2019 Unsupervised label noise modeling and loss correction☆223Updated 4 years ago
- Official Implementation of Early-Learning Regularization Prevents Memorization of Noisy Labels☆295Updated 2 years ago
- An efficient implicit semantic augmentation method, complementary to existing non-semantic techniques.☆590Updated 4 years ago
- Unofficial PyTorch Reimplementation of RandAugment.☆636Updated 2 years ago
- [ICLR2021 Oral] Free Lunch for Few-Shot Learning: Distribution Calibration☆472Updated 3 years ago
- A Survey☆562Updated 2 years ago
- mixup: Beyond Empirical Risk Minimization☆1,180Updated 3 years ago
- "In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning" by Mamshad Nayeem Riz…☆234Updated 2 years ago
- A PyTorch implementation of SimCLR based on ICML 2020 paper "A Simple Framework for Contrastive Learning of Visual Representations"☆558Updated 4 years ago
- ☆481Updated 7 months ago
- Unofficial PyTorch implementation of "Meta Pseudo Labels"☆387Updated last year