richardaecn / class-balanced-lossLinks
Class-Balanced Loss Based on Effective Number of Samples. CVPR 2019
☆612Updated 3 years ago
Alternatives and similar repositories for class-balanced-loss
Users that are interested in class-balanced-loss are comparing it to the libraries listed below
Sorting:
- Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"☆800Updated last year
- Pytorch implementation for "Large-Scale Long-Tailed Recognition in an Open World" (CVPR 2019 ORAL)☆867Updated 3 years ago
- The official PyTorch implementation of paper BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition☆668Updated 2 years ago
- [NeurIPS 2019] Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss☆684Updated 3 years ago
- This repository contains code for the paper "Decoupling Representation and Classifier for Long-Tailed Recognition", published at ICLR 202…☆975Updated 3 years ago
- Deep Metric Learning☆782Updated 4 years ago
- Implementation of the mixup training method☆466Updated 7 years ago
- Code for "MixMatch - A Holistic Approach to Semi-Supervised Learning"☆653Updated last year
- PyTorch Implementation for Deep Metric Learning Pipelines☆574Updated 5 years ago
- [NeurIPS 2020] This project provides a strong single-stage baseline for Long-Tailed Classification, Detection, and Instance Segmentation …☆570Updated 11 months ago
- A curated list of long-tailed recognition resources.☆586Updated 2 years ago
- 2.56%, 15.20%, 1.30% on CIFAR10, CIFAR100, and SVHN https://arxiv.org/abs/1708.04552☆550Updated 5 years ago
- Implementation of DropBlock: A regularization method for convolutional networks in PyTorch.☆596Updated 5 years ago
- Unsupervised Feature Learning via Non-parametric Instance Discrimination☆755Updated 4 years ago
- Code for reproducing Manifold Mixup results (ICML 2019)☆493Updated last year
- mixup: Beyond Empirical Risk Minimization☆1,185Updated 3 years ago
- Unofficial PyTorch Implementation of Unsupervised Data Augmentation.☆147Updated 4 years ago
- MS-Loss: Multi-Similarity Loss for Deep Metric Learning☆499Updated 2 years ago
- Unofficial PyTorch Reimplementation of RandAugment.☆636Updated 2 years ago
- PyTorch implementation of AutoAugment.☆159Updated 5 years ago
- [NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning☆756Updated 4 years ago
- NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels☆508Updated 3 years ago
- PyTorch implementation of Probabilistic End-to-end Noise Correction for Learning with Noisy Labels, CVPR 2019.☆139Updated 6 years ago
- Official implementation of 'FMix: Enhancing Mixed Sample Data Augmentation'☆338Updated 4 years ago
- PseudoLabel 2013, VAT, PI model, Tempens, MeanTeacher, ICT, MixMatch, FixMatch☆451Updated 2 years ago
- [ ECCV 2020 Spotlight ] Pytorch implementation for "Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets"☆369Updated 3 years ago
- Official Implementation of ICML 2019 Unsupervised label noise modeling and loss correction☆223Updated 5 years ago
- Learning Confidence for Out-of-Distribution Detection in Neural Networks☆275Updated 7 years ago
- PyTorch code for softmax variants: center loss, cosface loss, large-margin gaussian mixture, COCOLoss, ring loss☆255Updated 7 years ago
- ☆519Updated last year