mlsanityData to 14 Oct 2026

A Survey of Self-Supervised and Few-Shot Object Detection

arXiv 2110.14711 ↗First posted 27 Oct 2021cs.CV cs.AI cs.LGcited by 35

Not on the map. Why?

Abstract (arXiv)

Labeling data is often expensive and time-consuming, especially for tasks such as object detection and instance segmentation, which require dense labeling of the image. While few-shot object detection is about training a model on novel (unseen) object classes with little data, it still requires prior training on many labeled examples of base (seen) classes. On the other hand, self-supervised methods aim at learning representations from unlabeled data which transfer well to downstream tasks such as object detection. Combining few-shot and self-supervised object detection is a promising research direction. In this survey, we review and characterize the most recent approaches on few-shot and self-supervised object detection. Then, we give our main takeaways and discuss future research directions. Project page at https://gabrielhuang.github.io/fsod-survey/

Key facts. Cited by 35 papers in the map (data through 14 Oct 2026). Builds on 106 of its 153 references that are in the map. First posted on arXiv 27 Oct 2021.

Builds on

106 of 153 references.

References · 106

  1. 2017Attention Is All You Needcited by 60,361
  2. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  3. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  4. 2020Language Models are Few-Shot Learnerscited by 32,419
  5. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
  6. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  7. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  8. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,139
  9. 2020A Simple Framework for Contrastive Learning of Visual Representationscited by 12,049
  10. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,639
  11. 2018Representation Learning with Contrastive Predictive Codingcited by 7,777
  12. 2019Momentum Contrast for Unsupervised Visual Representation Learningcited by 7,513
38 more
  1. 2020End-to-End Object Detection with Transformerscited by 7,414
  2. 2017Mask R-CNNcited by 7,277
  3. 2021Emerging Properties in Self-Supervised Vision Transformerscited by 6,968
  4. 2016Feature Pyramid Networks for Object Detectioncited by 5,036
  5. 2017Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networkscited by 4,897
  6. 2014Fully Convolutional Networks for Semantic Segmentationcited by 4,859
  7. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,852
  8. 2020Bootstrap your own latent: A new approach to self-supervised Learningcited by 4,750
  9. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,375
  10. 2013Auto-Encoding Variational Bayescited by 4,053
  11. 2017MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applicationscited by 3,845
  12. 2020Deformable DETR: Deformable Transformers for End-to-End Object Detectioncited by 3,422
  13. 2015SSD: Single Shot MultiBox Detectorcited by 3,130
  14. 2017Prototypical Networks for Few-shot Learningcited by 3,015
  15. 2015Fast R-CNNcited by 2,933
  16. 2020Unsupervised Learning of Visual Features by Contrasting Cluster Assignmentscited by 2,857
  17. 2018YOLOv3: An Incremental Improvementcited by 2,659
  18. 2013Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distancescited by 2,316
  19. 2020Improved Baselines with Momentum Contrastive Learningcited by 2,287
  20. 2016Matching Networks for One Shot Learningcited by 2,255
  21. 2013Rich feature hierarchies for accurate object detection and semantic segmentationcited by 2,162
  22. 2021An Empirical Study of Training Self-Supervised Vision Transformerscited by 1,616
  23. 2018Unsupervised Representation Learning by Predicting Image Rotationscited by 1,591
  24. 2016Context Encoders: Feature Learning by Inpaintingcited by 1,428
  25. 2016Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzlescited by 1,382
  26. 2020Big Self-Supervised Models are Strong Semi-Supervised Learnerscited by 1,380
  27. 2019LVIS: A Dataset for Large Vocabulary Instance Segmentationcited by 1,217
  28. 2019Objects as Pointscited by 1,175
  29. 2017Learning to Compare: Relation Network for Few-Shot Learningcited by 1,143
  30. 2016Colorful Image Colorizationcited by 1,114
  31. 2015Unsupervised Visual Representation Learning by Context Predictioncited by 1,066
  32. 2016SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model sizecited by 1,060
  33. 2021Transformers in Vision: A Surveycited by 1,013
  34. 2021Scaling Vision Transformerscited by 999
  35. 2015Unsupervised Deep Embedding for Clustering Analysiscited by 767
  36. 2019A Closer Look at Few-shot Classificationcited by 684
  37. 2019Data-Efficient Image Recognition with Contrastive Predictive Codingcited by 673
  38. 2019Self-supervised Visual Feature Learning with Deep Neural Networks: A Surveycited by 657

50 most cited of 106 All 106 (JSON)

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 1; 2022: 7; 2023: 11; 2024: 7; 2025: 7; 2026: 2.

35 papers.

Sort:

By area:

  1. 2025YOLO26: Key Architectural Enhancements and Performance Benchmarking for Real-Time Object Detectioncited by 79
  2. 2023BlackVIP: Black-Box Visual Prompting for Robust Transfer Learningcited by 70
  3. 2021Few-Shot Object Detection: A Comprehensive Surveycited by 29
  4. 2022Continual Object Detection: A review of definitions, strategies, and challengescited by 25
  5. 2022Rethinking Few-Shot Object Detection on a Multi-Domain Benchmarkcited by 17
  6. 2023Towards Task Sampler Learning for Meta-Learningcited by 11
  7. 2024Few-Shot Object Detection: Research Advances and Challengescited by 11
  8. 2022Recent Few-Shot Object Detection Algorithms: A Survey with Performance Comparisoncited by 8
  9. 2023Oriented object detection in optical remote sensing images using deep learning: a surveycited by 8
  10. 2022Empirical Evaluation and Theoretical Analysis for Representation Learning: A Surveycited by 5
  11. 2023Few-shot Object Detection in Remote Sensing: Lifting the Curse of Incompletely Annotated Novel Objectscited by 5
  12. 2024Controllable Image Synthesis of Industrial Data Using Stable Diffusioncited by 5
23 more
  1. 2024MutDet: Mutually Optimizing Pre-training for Remote Sensing Object Detectioncited by 5
  2. 2024Unsupervised Object Discovery: A Comprehensive Survey and Unified Taxonomycited by 4
  3. 2024Robust Adaptation of Foundation Models with Black-Box Visual Promptingcited by 3
  4. 2025Self-Supervised Learning for Image Segmentation: A Comprehensive Surveycited by 3
  5. 2023Efficient Masked Autoencoders with Self-Consistencycited by 2
  6. 2023Make Explicit Calibration Implicit: Calibrate Denoiser Instead of the Noise Modelcited by 2
  7. 2024Self-Supervised Learning for Real-World Object Detection: a Surveycited by 2
  8. 2025Few-Shot Learning in Video and 3D Object Detection: A Surveycited by 2
  9. 2025Lacking Data? No worries! How synthetic images can alleviate image scarcity in wildlife surveys: a case study with muskox (Ovibos moschatus)cited by 2
  10. 2022A Unified Framework for Attention-Based Few-Shot Object Detectioncited by 1
  11. 2022A Comparative Attention Framework for Better Few-Shot Object Detection on Aerial Imagescited by 1
  12. 2023P3DC-Shot: Prior-Driven Discrete Data Calibration for Nearest-Neighbor Few-Shot Classificationcited by 1
  13. 2023MV-MR: multi-views and multi-representations for self-supervised learning and knowledge distillationcited by 1
  14. 2023Building Flyweight FLIM-based CNNs with Adaptive Decoding for Object Detectioncited by 1
  15. 2023IAdet: Simplest human-in-the-loop object detectioncited by 1
  16. 2025Mitigating Knowledge Discrepancies among Multiple Datasets for Task-agnostic Unified Face Alignmentcited by 1
  17. 2022Unifying Tracking and Image-Video Object Detectioncited by 0
  18. 2023Towards Few-Annotation Learning in Computer Vision: Application to Image Classification and Object Detection taskscited by 0
  19. 2024Improve Cross-domain Mixed Sampling with Guidance Training for Adaptive Segmentationcited by 0
  20. 2025An Empirical Study of Methods for Small Object Detection from Satellite Imagerycited by 0
  21. 2025Object-Centric Data Synthesis for Category-level Object Detectioncited by 0
  22. 2026An Annotation-to-Detection Framework for Autonomous and Robust Vine Trunk Localization in the Field by Mobile Agricultural Robotscited by 0
  23. 2026HQ-JEPA: Hybrid Quantum Joint-Embedding Predictive Architecture for Cross-Modal Remote Sensing Representation Learningcited by 0