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S4L: Self-Supervised Semi-Supervised Learning

arXiv 1905.03670 ↗First posted 9 May 2019cs.CV cs.LGcited by 335

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Abstract (arXiv)

This work tackles the problem of semi-supervised learning of image classifiers. Our main insight is that the field of semi-supervised learning can benefit from the quickly advancing field of self-supervised visual representation learning. Unifying these two approaches, we propose the framework of self-supervised semi-supervised learning and use it to derive two novel semi-supervised image classification methods. We demonstrate the effectiveness of these methods in comparison to both carefully tuned baselines, and existing semi-supervised learning methods. We then show that our approach and existing semi-supervised methods can be jointly trained, yielding a new state-of-the-art result on semi-supervised ILSVRC-2012 with 10% of labels.

Key facts. Cited by 335 papers in the map (data through 14 Oct 2026). First posted on arXiv 9 May 2019.

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Citing papers per year: 2021: 116; 2022: 90; 2023: 60; 2024: 39; 2025: 24; 2026: 6.

335 papers.

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  1. 2021Barlow Twins: Self-Supervised Learning via Redundancy Reductioncited by 1,838
  2. 2021Scaling Vision Transformerscited by 999
  3. 2021ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biasescited by 484
  4. 2021In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learningcited by 301
  5. 2021A Survey on Deep Semi-supervised Learningcited by 251
  6. 2022FreeMatch: Self-adaptive Thresholding for Semi-supervised Learningcited by 232
  7. 2022Generalized Category Discoverycited by 211
  8. 2023A Survey on Self-supervised Learning: Algorithms, Applications, and Future Trendscited by 207
  9. 2021ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentationcited by 184
  10. 2021Open-World Semi-Supervised Learningcited by 165
  11. 2021SCARF: Self-Supervised Contrastive Learning using Random Feature Corruptioncited by 156
  12. 2021Semantic Segmentation with Generative Models: Semi-Supervised Learning and Strong Out-of-Domain Generalizationcited by 141
38 more
  1. 2021SEED: Self-supervised Distillation For Visual Representationcited by 134
  2. 2022SimMatch: Semi-supervised Learning with Similarity Matchingcited by 118
  3. 2021Humble Teachers Teach Better Students for Semi-Supervised Object Detectioncited by 116
  4. 2021AutoNovel: Automatically Discovering and Learning Novel Visual Categoriescited by 116
  5. 2021Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samplescited by 114
  6. 2022Parametric Classification for Generalized Category Discovery: A Baseline Studycited by 113
  7. 2021Semi-supervised Semantic Segmentation with Directional Context-aware Consistencycited by 112
  8. 20213D Human Action Representation Learning via Cross-View Consistency Pursuitcited by 106
  9. 2021Pixel Contrastive-Consistent Semi-Supervised Semantic Segmentationcited by 101
  10. 2022USB: A Unified Semi-supervised Learning Benchmark for Classificationcited by 95
  11. 2023Dynamic Conceptional Contrastive Learning for Generalized Category Discoverycited by 92
  12. 2021Guided Point Contrastive Learning for Semi-supervised Point Cloud Semantic Segmentationcited by 87
  13. 2022PromptCAL: Contrastive Affinity Learning via Auxiliary Prompts for Generalized Novel Category Discoverycited by 87
  14. 2021Divide and Contrast: Self-supervised Learning from Uncurated Datacited by 85
  15. 2021Weakly Supervised Contrastive Learningcited by 81
  16. 2021PixMatch: Unsupervised Domain Adaptation via Pixelwise Consistency Trainingcited by 80
  17. 2021Exponential Moving Average Normalization for Self-supervised and Semi-supervised Learningcited by 78
  18. 2021A Broad Study on the Transferability of Visual Representations with Contrastive Learningcited by 78
  19. 2021Self-Supervised Learning with Kernel Dependence Maximizationcited by 77
  20. 2022Knowledge Tracing: A Surveycited by 77
  21. 2022Divergence-aware Federated Self-Supervised Learningcited by 73
  22. 2021Unsupervised Object-Level Representation Learning from Scene Imagescited by 72
  23. 2023To Compress or Not to Compress- Self-Supervised Learning and Information Theory: A Reviewcited by 72
  24. 2023Learning Semi-supervised Gaussian Mixture Models for Generalized Category Discoverycited by 72
  25. 2021Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labelscited by 69
  26. 2021Mining Latent Classes for Few-shot Segmentationcited by 69
  27. 2021Collaborative Unsupervised Visual Representation Learning from Decentralized Datacited by 69
  28. 2022Pushing the limits of self-supervised ResNets: Can we outperform supervised learning without labels on ImageNet?cited by 67
  29. 2022Prompt Consistency for Zero-Shot Task Generalizationcited by 67
  30. 2021ABC: Auxiliary Balanced Classifier for Class-imbalanced Semi-supervised Learningcited by 65
  31. 2021What If We Only Use Real Datasets for Scene Text Recognition? Toward Scene Text Recognition With Fewer Labelscited by 63
  32. 2021What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments?cited by 63
  33. 2021Skeleton Cloud Colorization for Unsupervised 3D Action Representation Learningcited by 58
  34. 2021Pareto Self-Supervised Training for Few-Shot Learningcited by 52
  35. 2022Semi-Supervised and Unsupervised Deep Visual Learning: A Surveycited by 52
  36. 2022Pushing the limits of raw waveform speaker recognitioncited by 51
  37. 2021Semi-Supervised Action Recognition with Temporal Contrastive Learningcited by 50
  38. 2022Semi-supervised Vision Transformers at Scalecited by 49

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