There are 1 repository under pseudo-labeling topic.
code released for our ICML 2020 paper "Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation"
PyTorch open-source toolbox for unsupervised or domain adaptive object re-ID.
Winning solution for the Kaggle TGS Salt Identification Challenge.
A full pipeline AutoML tool for tabular data
Labelling platform for text using weak supervision.
"In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning" by Mamshad Nayeem Rizve, Kevin Duarte, Yogesh S Rawat, Mubarak Shah (ICLR 2021)
[NAACL 2021] This is the code for our paper `Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach'.
Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noisy Student Training
[IJCAI 2022] Official Pytorch code for paper “S2 Transformer for Image Captioning”
Weakly supervised medical named entity classification
Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling
Semi-Supervised Hyperspectral Image Classification
[NeurIPS 2022] Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering
"Towards Realistic Semi-Supervised Learning" by Mamshad Nayeem Rizve, Navid Kardan, Mubarak Shah (ECCV 2022)
[IJCAI 2023] Co-training with High-Confidence Pseudo Labels for Semi-supervised Medical Image Segmentation
"OpenLDN: Learning to Discover Novel Classes for Open-World Semi-Supervised Learning" by Mamshad Nayeem Rizve, Navid Kardan, Salman Khan, Fahad Shahbaz Khan, Mubarak Shah (ECCV 2022)
The dataset for the paper 'Learning self-supervised traversability with navigation experiences of mobile robots: A risk-aware self-training approach'
[AAAI 2022] Label Hallucination for Few-Shot Classification
Creating datasets in YOLO format using pretrained YOLO model in Darknet framework which could be used to train the model further
Pseudo-labeling for tabular data
[ECCV2024] Mitigating Background Shift in Class-Incremental Semantic Segmentation
ISWC2020 Semantic Web Challenge - Product Classification Top1 Solution
[AAAI 2023] This is the code for our paper `Neighborhood-Regularized Self-Training for Learning with Few Labels'.
IFSS-Net: Interactive Few-Shot Siamese Network for Faster Muscle Segmentation and Propagation in Volumetric Ultrasound
This repo contains implementation of uncertainty estimation, rectification, and minimization for guiding the pseudo-label learning in semi-supervised defect segmentation setting.
Source code and data for the journal ``Dual learning for semi-supervised natural language understanding" in TASLP 2020.
"Advanced Machine Learning" project @ Politecnico di Torino, a.y. 2021/2022.
This repo contains implementation of semi-supervised defect segmentation based on pairwise similarity map consistency and ensemble-based cross pseudo labels
An Uncertainty-Aware Pseudo-Label Selection Framework using Regularized Conformal Prediction
Research paper-Enhancing action recognition with precondition and effect
auto_labeler - An all-in-one library to automatically label vision data
You can’t handle the (dirty) truth: Data-centric insights improve pseudo-labeling