naver-ai / cmoLinks
☆48Updated 2 years ago
Alternatives and similar repositories for cmo
Users that are interested in cmo are comparing it to the libraries listed below
Sorting:
- Official Pytorch implementation of "Learning Debiased Representation via Disentangled Feature Augmentation (Neurips 2021, Oral)"☆105Updated 2 years ago
- Official PyTorch implementation of MIRO (ECCV 2022)☆88Updated 3 years ago
- SaliencyMix: A Saliency Guided Data Augmentation Strategy for Better Regularization☆49Updated 3 years ago
- ☆22Updated 3 years ago
- NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"☆41Updated 4 years ago
- Official Implementation of SWAD (NeurIPS 2021)☆170Updated 3 years ago
- ☆31Updated 8 months ago
- ☆60Updated 2 years ago
- the code for paper "Energy-Based Open-World Uncertainty Modeling for Confidence Calibration"☆41Updated 4 years ago
- Improving Calibration for Long-Tailed Recognition (CVPR2021)☆153Updated 4 years ago
- Code Release for "Self-supervised Learning is More Robust to Dataset Imbalance"☆39Updated 3 years ago
- MOS: Towards Scaling Out-of-distribution Detection for Large Semantic Space☆98Updated 4 years ago
- Code for the ICLR2022 paper on Subspace Regularization for few-shot class incremental image classification☆30Updated 2 years ago
- Pytorch implementation for "Towards Realistic Long-Tailed Semi-Supervised Learning: Consistency Is All You Need" (CVPR 2023)☆71Updated 2 years ago
- [CVPR2023] Global and Local Mixture Consistency Cumulative Learning for Long-tailed Visual Recognitions☆76Updated 2 years ago
- PyTorch implementation of Self-supervised Contrastive Regularization for DG (SelfReg) [ICCV2021]☆78Updated 3 years ago
- ☆33Updated 4 years ago
- ☆60Updated 3 years ago
- [CVPR'22] Official Implementation of the CVPR 2022 paper "UNICON: Combating Label Noise Through Uniform Selection and Contrastive Learnin…☆63Updated last year
- CVPR 2022: Selective-Supervised Contrastive Learning with Noisy Labels☆95Updated 3 years ago
- [CVPR 2022] Pytorch implementation for “Debiased Learning from Naturally Imbalanced Pseudo-Labels”☆105Updated 4 months ago
- Reducing Domain Gap by Reducing Style Bias (SagNets)☆103Updated 4 years ago
- PyTorch code for the ICCV'21 paper: "Always Be Dreaming: A New Approach for Class-Incremental Learning"☆64Updated 3 years ago
- ☆19Updated 3 years ago
- Code for "Interpretable image classification with differentiable prototypes assignment", ECCV 2022☆28Updated 3 years ago
- (NeurIPS 2020 Workshop on SSL) Official Implementation of "MixCo: Mix-up Contrastive Learning for Visual Representation"☆58Updated 3 years ago
- ☆19Updated 3 years ago
- Repository for the paper `DASO: Distribution-Aware Semantics-Oriented Pseudo-label Imbalanced Semi-Supervised Learning'.☆73Updated 3 years ago
- ☆27Updated 3 years ago
- ICLR 2021 i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning☆80Updated 2 years ago