Papers with Code 아카이브

Semi Supervised Learning for Image Captioning

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하위 태스크: 1
평가표: 3
보존된 평가 기록: 3

코드

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

https://github.com/microsoft/ProDA

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

https://github.com/microsoft/SoftTeacher

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End-to-End Semi-Supervised Object Detection with Soft Teacher

https://github.com/milkxie/ssmll-cap

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Class-Distribution-Aware Pseudo Labeling for Semi-Supervised Multi-Label Learning

https://github.com/mingukjang/tast

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Test-Time Adaptation via Self-Training with Nearest Neighbor Information

https://github.com/mlspeech/gradseg

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Unsupervised Word Segmentation Using Temporal Gradient Pseudo-Labels

https://github.com/moucheng2017/emssl

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Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi-Supervised Segmentation

https://github.com/movinghoon/mira

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Unsupervised Visual Representation Learning via Mutual Information Regularized Assignment

https://github.com/mu-y/mpl-mdd

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Improving Mispronunciation Detection with Wav2vec2-based Momentum Pseudo-Labeling for Accentedness and Intelligibility Assessment

https://github.com/mxahan/nev-ncd

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Novel Categories Discovery Via Constraints on Empirical Prediction Statistics

https://github.com/mxbh/spatiotemporal-ssl

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Context Matters: Leveraging Spatiotemporal Metadata for Semi-Supervised Learning on Remote Sensing Images

https://github.com/nayeemrizve/trssl

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Towards Realistic Semi-Supervised Learning

https://github.com/nayeemrizve/ups

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In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning

https://github.com/nazmul-karim170/C-SFDA_Source-Free-Domain-Adaptation

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C-SFDA: A Curriculum Learning Aided Self-Training Framework for Efficient Source Free Domain Adaptation

https://github.com/nhcha6/classdistributionprediction

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Predicting Class Distribution Shift for Reliable Domain Adaptive Object Detection

https://github.com/niamhbelton/ss-fewsome_disease_severity_knee_osteoarthritis

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An AI System for Continuous Knee Osteoarthritis Severity Grading Using Self-Supervised Anomaly Detection with Limited Data

https://github.com/nini0919/semires

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SAM as the Guide: Mastering Pseudo-Label Refinement in Semi-Supervised Referring Expression Segmentation

https://github.com/nini0919/sspng

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Semi-Supervised Panoptic Narrative Grounding

https://github.com/nust-machine-intelligence-laboratory/i2crc

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Saliency Guided Inter- and Intra-Class Relation Constraints for Weakly Supervised Semantic Segmentation

https://github.com/nust-machine-intelligence-laboratory/torchsemiseg2

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Semi-Supervised Semantic Segmentation With Region Relevance

https://github.com/oiplab-dut/mfnet

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MFNet: Multi-filter Directive Network for Weakly Supervised Salient Object Detection

https://github.com/open-mmlab/OpenSelfSup

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Delving into Inter-Image Invariance for Unsupervised Visual Representations

https://github.com/open-mmlab/mmselfsup

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Delving into Inter-Image Invariance for Unsupervised Visual Representations

https://github.com/ortonwang/plgdf

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Pseudo Label-Guided Data Fusion and Output Consistency for Semi-Supervised Medical Image Segmentation

https://github.com/ortonwang/scribblevs

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ScribbleVS: Scribble-Supervised Medical Image Segmentation via Dynamic Competitive Pseudo Label Selection

https://github.com/osmanberke/sfda-ssvep-bci

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Source-Free Domain Adaptation for SSVEP-based Brain-Computer Interfaces

https://github.com/p-karisani/self_pretraining

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Semi-Supervised Text Classification via Self-Pretraining

https://github.com/pascalschlachter/planalysis

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Analysis of Pseudo-Labeling for Online Source-Free Universal Domain Adaptation

https://github.com/paulalbert31/pls

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Is your noise correction noisy? PLS: Robustness to label noise with two stage detection

https://github.com/paulalbert31/sncf

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Is your noise correction noisy? PLS: Robustness to label noise with two stage detection

https://github.com/pixel-333/MRCMV

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Deep Music Retrieval for Fine-Grained Videos by Exploiting Cross-Modal-Encoded Voice-Overs

https://github.com/pphub-hy/torch-tapnet

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Deep Learning based Intelligent Coin-tap Test for Defect Recognition

https://github.com/prantikbubun/beyond-pixels

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Beyond Pixels: Semi-Supervised Semantic Segmentation with a Multi-scale Patch-based Multi-Label Classifier

https://github.com/puchapu/utep

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Learning Unbiased Transferability for Domain Adaptation by Uncertainty Modeling

https://github.com/qdin4048/CPL-OT

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Conflict-Aware Pseudo Labeling via Optimal Transport for Entity Alignment

https://github.com/qiumuyang/siab

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The Devil is in the Statistics: Mitigating and Exploiting Statistics Difference for Generalizable Semi-supervised Medical Image Segmentation

https://github.com/qiurui4shu/PIG

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PIG: Prompt Images Guidance for Night-Time Scene Parsing

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