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Pseudo Label

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A lightweight but very power technique for semi supervised learning

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/rhfeiyang/SPPOT

공식 코드

SP$^2$OT: Semantic-Regularized Progressive Partial Optimal Transport for Imbalanced Clustering

https://github.com/rhfeiyang/ppot

공식 코드

P$^2$OT: Progressive Partial Optimal Transport for Deep Imbalanced Clustering

https://github.com/ricardooyoung/versatileteacher

공식 코드

Versatile Teacher: A Class-aware Teacher-student Framework for Cross-domain Adaptation

https://github.com/ruiyang-061x/lise

공식 코드

Approaching Outside: Scaling Unsupervised 3D Object Detection from 2D Scene

https://github.com/runminjiang/pw4medseg

공식 코드

Enhancing Weakly Supervised 3D Medical Image Segmentation through Probabilistic-aware Learning

https://github.com/rvandeghen/ASTOD

공식 코드

Adaptive Self-Training for Object Detection

https://github.com/sahar-nasiri/dist

공식 코드

Dual Invariance Self-training for Reliable Semi-supervised Surgical Phase Recognition

https://github.com/sahilkhose/FloodNet

공식 코드

Semi-Supervised Classification and Segmentation on High Resolution Aerial Images

https://github.com/sakura-not-sleep/ca_fvd

공식 코드

Consistency-aware Fake Videos Detection on Short Video Platforms

https://github.com/salah-zaiem/Pseudo-Label-Selection

공식 코드

Conditional independence for pretext task selection in Self-supervised speech representation learning

https://github.com/salesforce/inv-cdip

공식 코드

Field Extraction from Forms with Unlabeled Data

https://github.com/savinay95n/PatchRefineNet

공식 코드

PatchRefineNet: Improving Binary Segmentation by Incorporating Signals from Optimal Patch-wise Binarization

https://github.com/shakeebmurtaza/dips

공식 코드

DiPS: Discriminative Pseudo-Label Sampling with Self-Supervised Transformers for Weakly Supervised Object Localization

https://github.com/shengcao-cao/cmt

공식 코드

Contrastive Mean Teacher for Domain Adaptive Object Detectors

https://github.com/shigemichimatsuzaki/ms2pl

공식 코드

Multi-Source Soft Pseudo-Label Learning with Domain Similarity-based Weighting for Semantic Segmentation

https://github.com/shijiangming1/mmm

공식 코드

Multi-Memory Matching for Unsupervised Visible-Infrared Person Re-Identification

https://github.com/shishuaihu/prosfda

공식 코드

ProSFDA: Prompt Learning based Source-free Domain Adaptation for Medical Image Segmentation

https://github.com/shjo-april/recurseed_and_edgepredictmix

공식 코드

RecurSeed and EdgePredictMix: Pseudo-Label Refinement Learning for Weakly Supervised Semantic Segmentation across Single- and Multi-Stage Frameworks

https://github.com/shuchangye-bib/sgseg

공식 코드

SGSeg: Enabling Text-free Inference in Language-guided Segmentation of Chest X-rays via Self-guidance

https://github.com/shuvenduroy/ssl_fer

공식 코드

Analysis of Semi-Supervised Methods for Facial Expression Recognition

https://github.com/shuvenduroy/ssl_fer_ood

공식 코드

Exploring the Boundaries of Semi-Supervised Facial Expression Recognition using In-Distribution, Out-of-Distribution, and Unconstrained Data

https://github.com/siddiquemu/sct_mcta

공식 코드

Tracking Passengers and Baggage Items using Multiple Overhead Cameras at Security Checkpoints

https://github.com/siyi-wind/STiL

공식 코드

STiL: Semi-supervised Tabular-Image Learning for Comprehensive Task-Relevant Information Exploration in Multimodal Classification

https://github.com/snowdusky/dualpolishlearning

공식 코드

Mind the Gap: Polishing Pseudo labels for Accurate Semi-supervised Object Detection

https://github.com/solicucu/siod

공식 코드

SIOD: Single Instance Annotated Per Category Per Image for Object Detection

https://github.com/songxiaoshuai/dpl

공식 코드

Decoupling Pseudo Label Disambiguation and Representation Learning for Generalized Intent Discovery

https://github.com/ssi-research/sfda-rchc

공식 코드

Reconciling a Centroid-Hypothesis Conflict in Source-Free Domain Adaptation

https://github.com/stefan-maximilian-dietrich/reliable-pls

공식 코드

Semi-Supervised Learning guided by the Generalized Bayes Rule under Soft Revision

https://github.com/stone5265/3c-reid

공식 코드

3C: Confidence-Guided Clustering and Contrastive Learning for Unsupervised Person Re-Identification

https://github.com/strivezs/alps

공식 코드

ALPS: An Auto-Labeling and Pre-training Scheme for Remote Sensing Segmentation With Segment Anything Model

https://github.com/szbonaldo/fedmlp

공식 코드

FedMLP: Federated Multi-Label Medical Image Classification under Task Heterogeneity

https://github.com/taicaichen/pg-lbo

공식 코드

PG-LBO: Enhancing High-Dimensional Bayesian Optimization with Pseudo-Label and Gaussian Process Guidance

https://github.com/tencentyouturesearch/classification-semicls

공식 코드

Class-Aware Contrastive Semi-Supervised Learning

https://github.com/thu-bpm/gradlre

공식 코드

Gradient Imitation Reinforcement Learning for Low Resource Relation Extraction

https://github.com/thufdd/multi-mode-fault-diagnosis-datasets-with-te-process

공식 코드

An Evidential Real-Time Multi-Mode Fault Diagnosis Approach Based on Broad Learning System

https://github.com/tingxueronghua/dpke

공식 코드

Dual-Perspective Knowledge Enrichment for Semi-Supervised 3D Object Detection

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