Pinned Repositories
Awesome-Noisy-Labels
A Survey
CoOp
Prompt Learning for Vision-Language Models (IJCV'22, CVPR'22)
DMLP
Source code for our CVPR paper Learning from Noisy Labels with Decoupled Meta Label Purifier
JNPL
the implementation for the paper(Joint Negative and Positive Learning for Noisy Labels)
LC-Booster
Learning-to-Purify-Noisy-Labels-via-Meta-Soft-Label-Corrector
meta-weight-net
NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).
Meta-weight-net_class-imbalance
NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for class imbalance).
mixup
Implementation of the mixup training method
mixupfamily
The implementation of mixup and mainfold mixup method with standard models(PreActRes, WideRes, Dense) in Cifar10, Cifar100 and SVHN dataset on supervised(sl) and semi-supervised(ssl) tasks.
1326261060's Repositories
1326261060/Awesome-Noisy-Labels
A Survey
1326261060/CoOp
Prompt Learning for Vision-Language Models (IJCV'22, CVPR'22)
1326261060/DMLP
Source code for our CVPR paper Learning from Noisy Labels with Decoupled Meta Label Purifier
1326261060/JNPL
the implementation for the paper(Joint Negative and Positive Learning for Noisy Labels)
1326261060/LC-Booster
1326261060/Learning-to-Purify-Noisy-Labels-via-Meta-Soft-Label-Corrector
1326261060/mixup
Implementation of the mixup training method
1326261060/mixupfamily
The implementation of mixup and mainfold mixup method with standard models(PreActRes, WideRes, Dense) in Cifar10, Cifar100 and SVHN dataset on supervised(sl) and semi-supervised(ssl) tasks.
1326261060/MLC
Meta Label Correction for Noisy Label Learning
1326261060/NLNL-Negative-Learning-for-Noisy-Labels
NLNL: Negative Learning for Noisy Labels
1326261060/transferlearning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习