There are 1 repository under noisy-label-learning topic.
A curated (most recent) list of resources for Learning with Noisy Labels
The official implementation of the ACM MM'21 paper Co-learning: Learning from noisy labels with self-supervision.
[ICML2022 Long Talk] Official Pytorch implementation of "To Smooth or Not? When Label Smoothing Meets Noisy Labels"
Official implementation of the ECCV2022 paper: Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression Recognition
[ICLR2021] Official Pytorch implementation of "When Optimizing f-Divergence is Robust with Label noise"
MultiWOZ 2.4: A Multi-Domain Task-Oriented Dialogue Dataset
Official implementation of our NeurIPS2021 paper: Relative Uncertainty Learning for Facial Expression Recognition
(L2ID@CVPR2021, TNNLS2022) Boosting Co-teaching with Compression Regularization for Label Noise
Official codes for ACM CIKM '22 full paper: Towards Federated Learning against Noisy Labels via Local Self-Regularization
(Pattern Recognition Letters 2023) PyTorch implementation of "Jigsaw-ViT: Learning Jigsaw Puzzles in Vision Transformer"
NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"
Q. Yao, H. Yang, B. Han, G. Niu, J. Kwok. Searching to Exploit Memorization Effect in Learning from Noisy Labels. ICML 2020
[ICML'2022] Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network
[AAAI 2025] MonoBox: Tightness-free Box-supervised Polyp Segmentation using Monotonicity Constraint
Official codes for ACM CIKM '24 full paper: Tackling Noisy Clients in Federated Learning with End-to-end Label Correction
[cvpr2023] implementation of out-of-candidate rectification methods
Official codes for FNBench: Benchmarking Robust Federated Learning against Noisy Labels
Code for the paper "A Gift from Label Smoothing: Robust Training with Adaptive Label Smoothing via Auxiliary Classifier under Label Noise" (AAAI 2023)
[MICCAI'2023] Rectifying Noisy Labels with Sequential Prior: Multi-Scale Temporal Feature Affinity Learning for Robust Video Segmentation
Code for the KDD-2023 paper: Neural-Hidden-CRF: A Robust Weakly-Supervised Sequence Labeler
[PR23] The implementation of the paper ''Learning Visual Question Answering on Controlled Semantic Noisy Labels''
A TensorFlow implementation of "Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels"
This is the official code for C2MT: Cross-to-merge training with class balance strategy for learning with noisy labels
A python implementation of tree methods for learning with noisy labels.
Official Pytorch Implementation of CrossSplit (ICML 2023)
This is the official code for our submission in the expression track of ABAW 2023 competition as a part of CVPR 2023.
Code for "Long-tailed learning with in- and out-of-distribution noisy labels in the open-world (开放世界下带有分布内和分布外噪声的长尾学习)"
Applying various data engineering techniques into image classification task for KAIST DS801 term project
[ICCV 2025] Guiding Noisy Label Conditional Diffusion Models with Score-based Discriminator Correction
Distributed Learning on the real-world noisy dataset Clothing1M