mlsanityData to 7 Oct 2026

Generalized Few-Shot Object Detection without Forgetting

arXiv 2105.09491 ↗First posted 20 May 2021cs.CVcited by 88

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Abstract (arXiv)

Recently few-shot object detection is widely adopted to deal with data-limited situations. While most previous works merely focus on the performance on few-shot categories, we claim that detecting all classes is crucial as test samples may contain any instances in realistic applications, which requires the few-shot detector to learn new concepts without forgetting. Through analysis on transfer learning based methods, some neglected but beneficial properties are utilized to design a simple yet effective few-shot detector, Retentive R-CNN. It consists of Bias-Balanced RPN to debias the pretrained RPN and Re-detector to find few-shot class objects without forgetting previous knowledge. Extensive experiments on few-shot detection benchmarks show that Retentive R-CNN significantly outperforms state-of-the-art methods on overall performance among all settings as it can achieve competitive results on few-shot classes and does not degrade the base class performance at all. Our approach has demonstrated that the long desired never-forgetting learner is available in object detection.

Key facts. Cited by 88 papers in the map (data through 7 Oct 2026). Builds on 41 of its 50 references that are in the map. First posted on arXiv 20 May 2021.

Builds on

41 of 50 references.

References · 41

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  3. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  4. 2017Mask R-CNNcited by 7,259
  5. 2016Feature Pyramid Networks for Object Detectioncited by 5,021
  6. 2017Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networkscited by 4,861
  7. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,829
  8. 2015SSD: Single Shot MultiBox Detectorcited by 3,125
  9. 2017Prototypical Networks for Few-shot Learningcited by 3,001
  10. 2015Fast R-CNNcited by 2,930
  11. 2016Matching Networks for One Shot Learningcited by 2,246
  12. 2013Rich feature hierarchies for accurate object detection and semantic segmentationcited by 2,160
29 more
  1. 2017Gradient Episodic Memory for Continual Learningcited by 1,871
  2. 2019FCOS: Fully Convolutional One-Stage Object Detectioncited by 1,573
  3. 2017Learning to Compare: Relation Network for Few-Shot Learningcited by 1,139
  4. 2018CornerNet: Detecting Objects as Paired Keypointscited by 763
  5. 2019CenterNet: Keypoint Triplets for Object Detectioncited by 654
  6. 2019Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selectioncited by 539
  7. 2018Meta-Learning with Latent Embedding Optimizationcited by 476
  8. 2018Dynamic Few-Shot Visual Learning without Forgettingcited by 385
  9. 2019A Baseline for Few-Shot Image Classificationcited by 298
  10. 2020Frustratingly Simple Few-Shot Object Detectioncited by 280
  11. 2018Few-shot Object Detection via Feature Reweightingcited by 265
  12. 2018Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoderscited by 206
  13. 2019Few-Shot Object Detection with Attention-RPN and Multi-Relation Detectorcited by 206
  14. 2019SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learningcited by 194
  15. 2019Meta R-CNN : Towards General Solver for Instance-level Few-shot Learningcited by 182
  16. 2020Few-Shot Object Detection and Viewpoint Estimation for Objects in the Wildcited by 142
  17. 2017Few-Shot Image Recognition by Predicting Parameters from Activationscited by 122
  18. 2020Multi-Scale Positive Sample Refinement for Few-Shot Object Detectioncited by 116
  19. 2020Incremental Few-Shot Object Detectioncited by 102
  20. 2018RepMet: Representative-based metric learning for classification and one-shot object detectioncited by 85
  21. 2018LSTD: A Low-Shot Transfer Detector for Object Detectioncited by 77
  22. 2019One-Shot Object Detection with Co-Attention and Co-Excitationcited by 67
  23. 2017Visual Relationship Detection with Internal and External Linguistic Knowledge Distillationcited by 60
  24. 2020FGN: Fully Guided Network for Few-Shot Instance Segmentationcited by 46
  25. 2019Few-Shot Learning with Global Class Representationscited by 44
  26. 2018One-Shot Instance Segmentationcited by 43
  27. 2020BorderDet: Border Feature for Dense Object Detectioncited by 39
  28. 2020Context-Transformer: Tackling Object Confusion for Few-Shot Detectioncited by 27
  29. 2021IQDet: Instance-wise Quality Distribution Sampling for Object Detectioncited by 20

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 13; 2022: 35; 2023: 19; 2024: 11; 2025: 7; 2026: 3.

88 papers.

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  1. 2022Learning What Not to Segment: A New Perspective on Few-Shot Segmentationcited by 120
  2. 2021DETReg: Unsupervised Pretraining with Region Priors for Object Detectioncited by 76
  3. 2022Detecting and Understanding Harmful Memes: A Surveycited by 58
  4. 2022Few-shot Object Counting and Detectioncited by 55
  5. 2022Meta-DETR: Image-Level Few-Shot Detection with Inter-Class Correlation Exploitationcited by 48
  6. 2021Label, Verify, Correct: A Simple Few Shot Object Detection Methodcited by 43
  7. 2024Cross-Domain Few-Shot Object Detection via Enhanced Open-Set Object Detectorcited by 43
  8. 2021Few-Shot Object Detection via Association and DIscriminationcited by 39
  9. 2021A Survey of Self-Supervised and Few-Shot Object Detectioncited by 35
  10. 2022Few-shot Image Generation via Adaptation-Aware Kernel Modulationcited by 33
  11. 2023Revisiting Few-Shot Object Detection with Vision-Language Modelscited by 32
  12. 2021Few-Shot Object Detection: A Comprehensive Surveycited by 28
38 more
  1. 2022Sylph: A Hypernetwork Framework for Incremental Few-shot Object Detectioncited by 23
  2. 2023Few-Shot Object Detection via Variational Feature Aggregationcited by 22
  3. 2023DiGeo: Discriminative Geometry-Aware Learning for Generalized Few-Shot Object Detectioncited by 21
  4. 2023Generating Features with Increased Crop-related Diversity for Few-Shot Object Detectioncited by 21
  5. 2022FS-DETR: Few-Shot DEtection TRansformer with prompting and without re-trainingcited by 20
  6. 2022iFS-RCNN: An Incremental Few-shot Instance Segmentercited by 19
  7. 2021Which images to label for few-shot medical landmark detection?cited by 16
  8. 2022Semantic-aligned Fusion Transformer for One-shot Object Detectioncited by 13
  9. 2023Detect Everything with Few Examplescited by 13
  10. 2021AirDet: Few-Shot Detection without Fine-tuning for Autonomous Explorationcited by 12
  11. 2022Breaking Immutable: Information-Coupled Prototype Elaboration for Few-Shot Object Detectioncited by 12
  12. 2023Reference Twice: A Simple and Unified Baseline for Few-Shot Instance Segmentationcited by 12
  13. 2022Multi-Faceted Distillation of Base-Novel Commonality for Few-shot Object Detectioncited by 11
  14. 2022Learning to Discover and Detect Objectscited by 11
  15. 2021A Comparative Review of Recent Few-Shot Object Detection Algorithmscited by 10
  16. 2023NIFF: Alleviating Forgetting in Generalized Few-Shot Object Detection via Neural Instance Feature Forgingcited by 10
  17. 2024Fine-Grained Prototypes Distillation for Few-Shot Object Detectioncited by 10
  18. 2024AirShot: Efficient Few-Shot Detection for Autonomous Explorationcited by 10
  19. 2022Extending One-Stage Detection with Open-World Proposalscited by 9
  20. 2025No time to train! Training-Free Reference-Based Instance Segmentationcited by 9
  21. 2022Mobile Robot Manipulation using Pure Object Detectioncited by 8
  22. 2022Recent Few-Shot Object Detection Algorithms: A Survey with Performance Comparisoncited by 8
  23. 2022Hierarchical Few-Shot Object Detection: Problem, Benchmark and Methodcited by 8
  24. 2022Towards Generalized Few-Shot Open-Set Object Detectioncited by 8
  25. 2024SMILe: Leveraging Submodular Mutual Information For Robust Few-Shot Object Detectioncited by 8
  26. 2023Identification of Novel Classes for Improving Few-Shot Object Detectioncited by 7
  27. 2021A Survey of Deep Learning for Low-Shot Object Detectioncited by 6
  28. 2022tSF: Transformer-based Semantic Filter for Few-Shot Learningcited by 6
  29. 2023Generalized Few-Shot 3D Object Detection of LiDAR Point Cloud for Autonomous Drivingcited by 6
  30. 2024CRoFT: Robust Fine-Tuning with Concurrent Optimization for OOD Generalization and Open-Set OOD Detectioncited by 6
  31. 2025Generalized Semantic Contrastive Learning via Embedding Side Information for Few-Shot Object Detectioncited by 6
  32. 2021Dynamic Relevance Learning for Few-Shot Object Detectioncited by 5
  33. 2021Pose Adaptive Dual Mixup for Few-Shot Single-View 3D Reconstructioncited by 5
  34. 2022CFA: Constraint-based Finetuning Approach for Generalized Few-Shot Object Detectioncited by 5
  35. 2023Improved Region Proposal Network for Enhanced Few-Shot Object Detectioncited by 5
  36. 2024Search and Detect: Training-Free Long Tail Object Detection via Web-Image Retrievalcited by 5
  37. 2022Category-Agnostic 6D Pose Estimation with Conditional Neural Processescited by 4
  38. 2022Revisiting Few-Shot Learning from a Causal Perspectivecited by 4

50 most cited of 88 All 88 (JSON)