JasonZhang156 / awesome-mixed-sample-data-augmentation
A collection of awesome things about mixed sample data augmentation
☆131Updated 4 years ago
Alternatives and similar repositories for awesome-mixed-sample-data-augmentation:
Users that are interested in awesome-mixed-sample-data-augmentation are comparing it to the libraries listed below
- [CVPR 2021] Adaptive Consistency Regularization for Semi-Supervised Transfer Learning☆103Updated 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
- Code for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels"☆170Updated 3 years ago
- PyTorch implementation of consistency regularization methods for semi-supervised learning☆78Updated 4 years ago
- [AAAI 2021] Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning☆138Updated 4 years ago
- CVPR'20: Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization☆126Updated last year
- PyTorch implementation of the paper "Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels" in NIPS 2018☆126Updated 5 years ago
- When Does Label Smoothing Help?_pytorch_implementationimp☆125Updated 5 years ago
- [ ECCV 2020 Spotlight ] Pytorch implementation for "Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets"☆367Updated 2 years ago
- Official implementation of "Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning"☆153Updated 4 years ago
- ☆94Updated 4 years ago
- "In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning" by Mamshad Nayeem Riz…☆234Updated last year
- [ECCV2020] Knowledge Distillation Meets Self-Supervision☆236Updated 2 years ago
- [ICLR2021 Oral] Free Lunch for Few-Shot Learning: Distribution Calibration☆472Updated 3 years ago
- LaSO: Label-Set Operations networks for multi-label few-shot learning - official implementation☆86Updated last year
- PyTorch implementation of Probabilistic End-to-end Noise Correction for Learning with Noisy Labels, CVPR 2019.☆139Updated 5 years ago
- [NeurIPS 2020] Released code for Interventional Few-Shot Learning☆168Updated 3 years ago
- PyTorch implementation of “Negative Margin Matters: Understanding Margin in Few-shot Classification”☆150Updated 4 years ago
- Regularizing Class-wise Predictions via Self-knowledge Distillation (CVPR 2020)☆107Updated 4 years ago
- PyTorch implementation of Temporal Ensembling for Semi-Supervised Learning☆111Updated 6 years ago
- Unofficial PyTorch Implementation of Unsupervised Data Augmentation.☆146Updated 4 years ago
- [ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels☆136Updated 9 months ago
- Self-supervised Label Augmentation via Input Transformations (ICML 2020)☆106Updated 4 years ago
- 📜 Self-Supervised Learning from Images: Up-to-date reading list.☆198Updated 3 years ago
- Implementation of Adversarial Domain Adaptation with Domain Mixup (AAAI 2020 Oral).☆163Updated 4 years ago
- PseudoLabel 2013, VAT, PI model, Tempens, MeanTeacher, ICT, MixMatch, FixMatch☆450Updated 2 years ago
- Official Implementation of ICML 2019 Unsupervised label noise modeling and loss correction☆222Updated 4 years ago
- The implementation of "Self-Supervised Generalisation with Meta Auxiliary Learning" [NeurIPS 2019].☆174Updated 3 years ago
- Unofficial PyTorch implementation of "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence"☆48Updated 2 years ago
- Code release for "Self-Tuning for Data-Efficient Deep Learning" (ICML 2021)☆110Updated 3 years ago