TACJu / Bi-Sampling
This is the official PyTorch implementation of the paper "Rethinking Re-Sampling in Imbalanced Semi-Supervised Learning" (Ju He, Adam Kortylewski, Shaokang Yang, Shuai Liu, Cheng Yang, Changhu Wang, Alan Yuille).
☆27Updated 3 years ago
Alternatives and similar repositories for Bi-Sampling:
Users that are interested in Bi-Sampling are comparing it to the libraries listed below
- Code for the paper "Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning" (NeurIPS 20)☆72Updated 2 years ago
- pytorch implementation of ABC : Auxiliary Balanced Classifier for Class-imbalanced Semi-supervised Learning☆36Updated last month
- ☆47Updated last year
- Code Release for "Self-supervised Learning is More Robust to Dataset Imbalance"☆38Updated 2 years ago
- Code for "Balanced Knowledge Distillation for Long-tailed Learning"☆27Updated last year
- (NeurIPS 2020 Workshop on SSL) Official Implementation of "MixCo: Mix-up Contrastive Learning for Visual Representation"☆58Updated 2 years ago
- Improving Calibration for Long-Tailed Recognition (CVPR2021)☆146Updated 3 years ago
- ☆30Updated 2 years ago
- ☆22Updated 3 years ago
- Code for "Multi-Task Curriculum Framework for Open-Set Semi-Supervised Learning"☆23Updated 4 years ago
- ☆58Updated last year
- Class-Imbalanced Semi-Supervised Learning code☆11Updated 3 years ago
- [ECCV 2020] Learning from Extrinsic and Intrinsic Supervisions for Domain Generalization☆48Updated 2 years ago
- [ICCV 2023 Oral] IOMatch: Simplifying Open-Set Semi-Supervised Learning with Joint Inliers and Outliers Utilization☆48Updated 11 months ago
- official source code for the Paper: **Long-tailed Visual Recognition via Gaussian Clouded Logit Adjustment** based on Pytorch.☆38Updated 6 months ago
- [CVPR 2020] Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from a Domain Adaptation Perspective☆24Updated 4 years ago
- Tensorflow Implementation on Paper [AAAI2020]Semi-Supervised Learning under Class Distribution Mismatch☆15Updated 3 years ago
- the code for paper "Energy-Based Open-World Uncertainty Modeling for Confidence Calibration"☆41Updated 3 years ago
- NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"☆39Updated 3 years ago
- Implementation of Learning to Combine: Knowledge Aggregation for Multi-Source Domain Adaptation (ECCV 2020).☆69Updated 2 years ago
- Repository for the paper `DASO: Distribution-Aware Semantics-Oriented Pseudo-label Imbalanced Semi-Supervised Learning'.☆70Updated 2 years ago
- Code release for NeurIPS 2020 paper "Co-Tuning for Transfer Learning"☆40Updated 2 years ago
- Spatial Contrastive Learning for Few-Shot Classification (ECML/PKDD 2021).☆49Updated 2 years ago
- Code release of paper Debiased Self-Training for Semi-Supervised Learning (NeurIPS 2022 Oral)☆51Updated 2 years ago
- Code of our method MbLS (Margin-based Label Smoothing) for network calibration. To Appear at CVPR 2022. Paper : https://arxiv.org/abs/211…☆49Updated 2 years ago
- Source code for ICLR 2022 paper "Meta Discovery: Learning to Discover Novel Classes given Very Limited Data".☆17Updated last year
- Pytorch codes for NeurIPS 2021 paper titled "Dynamic Distillation Network for Cross-Domain Few-Shot Recognition with Unlabeled Data".☆29Updated 2 years ago
- Code release for "Cycle Self-Training for Domain Adaptation" (NeurIPS 2021)☆53Updated 3 years ago
- (L2ID@CVPR2021, TNNLS2022) Boosting Co-teaching with Compression Regularization for Label Noise☆47Updated last year
- [CVPR 2021] MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition☆62Updated 2 years ago