KentoNishi / Augmentation-for-LNL
[CVPR 2021] Code for "Augmentation Strategies for Learning with Noisy Labels".
☆113Updated 3 years ago
Alternatives and similar repositories for Augmentation-for-LNL:
Users that are interested in Augmentation-for-LNL are comparing it to the libraries listed below
- PyTorch implementation of "Contrast to Divide: self-supervised pre-training for learning with noisy labels"☆71Updated 4 years ago
- Official PyTorch implementation of "Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity" (ICLR'21 Oral)☆103Updated 3 years ago
- (L2ID@CVPR2021, TNNLS2022) Boosting Co-teaching with Compression Regularization for Label Noise☆48Updated 2 years ago
- ICLR 2021, "Learning with feature-dependent label noise: a progressive approach"☆43Updated 2 years ago
- Code for 'Joint Optimization Framework for Learning with Noisy Labels'☆38Updated 6 years ago
- Pretrained SimCLRv2 models in Pytorch☆105Updated 4 years ago
- PyTorch implementation of the paper "Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels" in NIPS 2018☆126Updated 5 years ago
- Un-Mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning.☆151Updated 2 years ago
- Unofficial PyTorch implementation of "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence"☆48Updated 2 years ago
- PyTorch implementation of Probabilistic End-to-end Noise Correction for Learning with Noisy Labels, CVPR 2019.☆139Updated 5 years ago
- Differentiable Data Augmentation Library☆123Updated 2 years ago
- [TPAMI2022 & NeurIPS2020] Official implementation of Self-Adaptive Training☆129Updated 3 years ago
- Improving Calibration for Long-Tailed Recognition (CVPR2021)☆147Updated 3 years ago
- Official PyTorch implementation of "Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup" (ICML'20)☆159Updated 3 years ago
- An implementation of "A Simple Framework for Contrastive Learning of Visual Representatoins" SimCLR☆33Updated 4 years ago
- CVPR'20: Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization☆126Updated last year
- SKD : Self-supervised Knowledge Distillation for Few-shot Learning☆97Updated last year
- ☆46Updated 4 years ago
- Official Implementation of Early-Learning Regularization Prevents Memorization of Noisy Labels☆295Updated last year
- Self-supervised Label Augmentation via Input Transformations (ICML 2020)☆106Updated 4 years ago
- When Does Label Smoothing Help?_pytorch_implementationimp☆125Updated 5 years ago
- Official implementation for: "Multi-Objective Interpolation Training for Robustness to Label Noise"☆39Updated 2 years ago
- ☆66Updated 2 years ago
- Exploring Simple Siamese Representation Learning☆60Updated 4 years ago
- (NeurIPS 2020 Workshop on SSL) Official Implementation of "MixCo: Mix-up Contrastive Learning for Visual Representation"☆58Updated 2 years ago
- This is the repo for the paper "Episodic Training for Domain Generalization" https://arxiv.org/abs/1902.00113☆58Updated last year
- [NeurIPS'20] GradAug: A New Regularization Method for Deep Neural Networks☆93Updated 4 years ago
- Official code for the CVPR 2021 paper "How Well Do Self-Supervised Models Transfer?"☆183Updated last year
- ☆28Updated 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