pseudo-labeling 开源项目推荐（112 个）

tim-learn /SHOT

code released for our ICML 2020 paper "Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation"

open-mmlab /OpenUnReID

PyTorch open-source toolbox for unsupervised or domain adaptive object re-ID.

DataCanvasIO /HyperGBM

A full pipeline AutoML tool for tabular data

ybabakhin /kaggle_salt_bes_phalanx

Kaggle TGS 盐类识别挑战的获胜解决方案。

SeuTao /TGS-Salt-Identification

TGS盐识别

dataqa /nlp-labelling

Labelling platform for text using weak supervision.

nayeemrizve /ups

"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)

yueyu1030 /COSINE

[NAACL 2021] This is the code for our paper `Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach'.

sidgan /ETCI-2021-Competition-on-Flood-Detection

Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noisy Student Training

fcjian /PromptDet

PromptDet: Towards Open-vocabulary Detection using Uncurated Images, ECCV2022

zchoi /S2-Transformer

[IJCAI 2022] Official Pytorch code for paper “S2 Transformer for Image Captioning”

som-shahlab /trove

Weakly supervised medical named entity classification

Ikhyeon-Cho /TraverseSet

TraverseSet: A LiDAR-inertial dataset for self-supervised traversability learning in urban and rural environments [RA-L '24]

hellowangqian /domain-adaptation-capls

Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling

Senyh /UCMT

[IJCAI 2023] Co-training with High-Confidence Pseudo Labels for Semi-supervised Medical Image Segmentation

Gorilla-Lab-SCUT /TTAC

[NeurIPS 2022] Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering

majidseydgar /Res-CP

Semi-Supervised Hyperspectral Image Classification

nayeemrizve /TRSSL

"Towards Realistic Semi-Supervised Learning" by Mamshad Nayeem Rizve, Navid Kardan, Mubarak Shah (ECCV 2022)

GilhanPark /ECCV2024_MBS

[ECCV2024] Mitigating Background Shift in Class-Incremental Semantic Segmentation

nayeemrizve /OpenLDN

"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)