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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/liamheng/annotation-free-medical-image-enhancement

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Enhancing and Adapting in the Clinic: Source-free Unsupervised Domain Adaptation for Medical Image Enhancement

https://github.com/liangzid/TEMP

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Healing Unsafe Dialogue Responses with Weak Supervision Signals

https://github.com/lingrayy/plpb

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Robust Source-Free Domain Adaptation for Fundus Image Segmentation

https://github.com/lipang/special

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SPECIAL: Zero-shot Hyperspectral Image Classification With CLIP

https://github.com/lishenglana/gdstrack

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Modality-Guided Dynamic Graph Fusion and Temporal Diffusion for Self-Supervised RGB-T Tracking

https://github.com/liulisixin/mli-nerf

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MLI-NeRF: Multi-Light Intrinsic-Aware Neural Radiance Fields

https://github.com/liuzhengzhe/One-Thing-One-Click

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You Only Need One Thing One Click: Self-Training for Weakly Supervised 3D Scene Understanding

https://github.com/lixinustc/samb-transformeruda

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Semantic-aware Message Broadcasting for Efficient Unsupervised Domain Adaptation

https://github.com/lizhuohong/paraformer

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Learning without Exact Guidance: Updating Large-scale High-resolution Land Cover Maps from Low-resolution Historical Labels

https://github.com/lizzy8587/castdet

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Exploiting Unlabeled Data with Multiple Expert Teachers for Open Vocabulary Aerial Object Detection and Its Orientation Adaptation

https://github.com/lliuz/mixteacher

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MixTeacher: Mining Promising Labels with Mixed Scale Teacher for Semi-Supervised Object Detection

https://github.com/lofrienger/s2me

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S$^2$ME: Spatial-Spectral Mutual Teaching and Ensemble Learning for Scribble-supervised Polyp Segmentation

https://github.com/lokhande-vishnu/DeepHermites

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Generating Accurate Pseudo-labels in Semi-Supervised Learning and Avoiding Overconfident Predictions via Hermite Polynomial Activations

https://github.com/lseventeen/flare22-twostagephtrans

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Combining Self-Training and Hybrid Architecture for Semi-supervised Abdominal Organ Segmentation

https://github.com/lucasyang567/metaocc

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MetaOcc: Surround-View 4D Radar and Camera Fusion Framework for 3D Occupancy Prediction with Dual Training Strategies

https://github.com/luluho1208/diffusion-ss3d

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Diffusion-SS3D: Diffusion Model for Semi-supervised 3D Object Detection

https://github.com/luogen1996/oneteacher

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Towards End-to-end Semi-supervised Learning for One-stage Object Detection

https://github.com/luohongyin/entst

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Entailment as Robust Self-Learner

https://github.com/luyvlei/BiSMAPs

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Bidirectional Self-Training with Multiple Anisotropic Prototypes for Domain Adaptive Semantic Segmentation

https://github.com/lxysl/plremix

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PLReMix: Combating Noisy Labels with Pseudo-Label Relaxed Contrastive Representation Learning

https://github.com/machengcheng2016/crossteaching-ssod

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CrossRectify: Leveraging Disagreement for Semi-supervised Object Detection

https://github.com/mansoor-at/semi-supervised-surgical-tool-detection

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A semi-supervised Teacher-Student framework for surgical tool detection and localization

https://github.com/matinmoezzi/ups_conformal_classification

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An Uncertainty-Aware Pseudo-Label Selection Framework using Regularized Conformal Prediction

https://github.com/matsuo-shinnosuke/online-pseudo-labeling

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Learning from Label Proportion with Online Pseudo-Label Decision by Regret Minimization

https://github.com/matthewcym/sflm

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Revisiting Self-Training for Few-Shot Learning of Language Model

https://github.com/mattochal/enhanced-outlier-logits

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EOL: Transductive Few-Shot Open-Set Recognition by Enhancing Outlier Logits

https://github.com/megvii-basedetection/denseteacher

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Dense Teacher: Dense Pseudo-Labels for Semi-supervised Object Detection

https://github.com/megvii-research/co-mining

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Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection

https://github.com/megvii-research/fullmatch

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Boosting Semi-Supervised Learning by Exploiting All Unlabeled Data

https://github.com/meitounao110/uge-st

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Uncertainty Guided Ensemble Self-Training for Semi-Supervised Global Field Reconstruction

https://github.com/mesophil/myriadal

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MyriadAL: Active Few Shot Learning for Histopathology

https://github.com/miaomiaoli2/ruleprompt

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RulePrompt: Weakly Supervised Text Classification with Prompting PLMs and Self-Iterative Logical Rules

https://github.com/miccaiif/dgmil

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DGMIL: Distribution Guided Multiple Instance Learning for Whole Slide Image Classification

https://github.com/miccaiif/ins

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Rethinking Multiple Instance Learning for Whole Slide Image Classification: A Good Instance Classifier is All You Need

https://github.com/michaelvorndran/inconsistencymasks

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Inconsistency Masks: Removing the Uncertainty from Input-Pseudo-Label Pairs

https://github.com/microsoft/ProDA

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Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation

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