Papers with Code 아카이브

Semi-Supervised Image Classification

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크: 2
평가표: 59
보존된 평가 기록: 456

Semi-supervised image classification leverages unlabelled data as well as labelled data to increase classification performance.

You may want to read some blog posts to get an overview before reading the papers and checking the leaderboards:

An overview of proxy-label approaches for semi-supervised learning - Sebastian Ruder
Semi-Supervised Learning in Computer Vision - Amit Chaudhary

<span style="color:grey; opacity: 0.6">( Image credit: Self-Supervised Semi-Supervised Learning )</span>

코드

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

https://github.com/CuriousAI/mean-teacher

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Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results

https://github.com/DoctorKey/R2D2.pytorch

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Repetitive Reprediction Deep Decipher for Semi-Supervised Learning

https://github.com/King-HAW/DC-MT

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A Self-ensembling Framework for Semi-supervised Knee Cartilage Defects Assessment with Dual-Consistency

https://github.com/KyleZheng1997/WCL

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Weakly Supervised Contrastive Learning

https://github.com/LiheYoung/ShrinkMatch

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Shrinking Class Space for Enhanced Certainty in Semi-Supervised Learning

https://github.com/MarziEd/SubSpace-Capsule-Network

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Subspace Capsule Network

https://github.com/NJUyued/MutexMatch4SSL

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MutexMatch: Semi-Supervised Learning with Mutex-Based Consistency Regularization

https://github.com/Na-Z/sess

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SESS: Self-Ensembling Semi-Supervised 3D Object Detection

https://github.com/PaperCodeSubmission/AAAI2021-260

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SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations

https://github.com/SYangDong/tse-t

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Temporal Self-Ensembling Teacher for Semi-Supervised Object Detection

https://github.com/Shu1L0n9/SemiOccam

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ViTSGMM: A Robust Semi-Supervised Image Recognition Network Using Sparse Labels

https://github.com/TonyLianLong/UnsupervisedSelectiveLabeling

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Unsupervised Selective Labeling for More Effective Semi-Supervised Learning

https://github.com/Valentyn1997/oct-diagn-semi-supervised

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Matching the Clinical Reality: Accurate OCT-Based Diagnosis From Few Labels

https://github.com/Westlake-AI/SemiReward

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SemiReward: A General Reward Model for Semi-supervised Learning

https://github.com/Westlake-AI/openmixup

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OpenMixup: Open Mixup Toolbox and Benchmark for Visual Representation Learning

https://github.com/ZHKKKe/DualStudent

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Dual Student: Breaking the Limits of the Teacher in Semi-supervised Learning

https://github.com/amazon-research/exponential-moving-average-normalization

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Exponential Moving Average Normalization for Self-supervised and Semi-supervised Learning

https://github.com/arasmus/ladder

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Semi-Supervised Learning with Ladder Networks

https://github.com/attaullah/Self-training/blob/master/Transfer_learning.md

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Transfer of Pretrained Model Weights Substantially Improves Semi-Supervised Image Classification

https://github.com/attaullah/downsampled-plant-disease-dataset

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Transfer of Pretrained Model Weights Substantially Improves Semi-Supervised Image Classification

https://github.com/ayaanzhaque/EC-GAN

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EC-GAN: Low-Sample Classification using Semi-Supervised Algorithms and GANs

https://github.com/beandkay/epass

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Debiasing, calibrating, and improving Semi-supervised Learning performance via simple Ensemble Projector

https://github.com/beandkay/sequencematch

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SequenceMatch: Revisiting the design of weak-strong augmentations for Semi-supervised learning

https://github.com/benathi/fastswa-semi-sup

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There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average

https://github.com/boazlern/SSClustering

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Boosting the Performance of Semi-Supervised Learning with Unsupervised Clustering

https://github.com/bytedance/TWIST

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Self-Supervised Learning by Estimating Twin Class Distributions

https://github.com/bytedance/ibot

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iBOT: Image BERT Pre-Training with Online Tokenizer

https://github.com/chenhsing/ssp3d

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Semi-Supervised Single-View 3D Reconstruction via Prototype Shape Priors

https://github.com/chenhsing/svformer

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SVFormer: Semi-supervised Video Transformer for Action Recognition

https://github.com/chenmc1996/Multi-Head-Co-Training

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Semi-Supervised Learning with Multi-Head Co-Training

https://github.com/cvmi-lab/simgcd

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Parametric Classification for Generalized Category Discovery: A Baseline Study

https://github.com/deeplearning-wisc/sorl

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A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning

https://github.com/deepmind/deepmind-research/tree/master/byol

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Bootstrap your own latent: A new approach to self-supervised Learning

https://github.com/doerlbh/BerlinUCB

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Online Semi-Supervised Learning in Contextual Bandits with Episodic Reward

https://github.com/edenton/cc-gan

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Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks

https://github.com/emannix/cold-paws-labelling-selection-strategies

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Cold PAWS: Unsupervised class discovery and addressing the cold-start problem for semi-supervised learning

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.