mlsanityData to 14 Oct 2026

Few-Shot Object Detection with Fully Cross-Transformer

arXiv 2203.15021 ↗First posted 28 Mar 2022cs.CV cs.AI cs.MMcited by 64

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Abstract (arXiv)

Few-shot object detection (FSOD), with the aim to detect novel objects using very few training examples, has recently attracted great research interest in the community. Metric-learning based methods have been demonstrated to be effective for this task using a two-branch based siamese network, and calculate the similarity between image regions and few-shot examples for detection. However, in previous works, the interaction between the two branches is only restricted in the detection head, while leaving the remaining hundreds of layers for separate feature extraction. Inspired by the recent work on vision transformers and vision-language transformers, we propose a novel Fully Cross-Transformer based model (FCT) for FSOD by incorporating cross-transformer into both the feature backbone and detection head. The asymmetric-batched cross-attention is proposed to aggregate the key information from the two branches with different batch sizes. Our model can improve the few-shot similarity learning between the two branches by introducing the multi-level interactions. Comprehensive experiments on both PASCAL VOC and MSCOCO FSOD benchmarks demonstrate the effectiveness of our model.

Key facts. Cited by 64 papers in the map (data through 14 Oct 2026). Builds on 43 of its 53 references that are in the map. First posted on arXiv 28 Mar 2022.

Builds on

43 of 53 references.

References · 43

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31 more
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  27. 2021Dense Relation Distillation with Context-aware Aggregation for Few-Shot Object Detectioncited by 53
  28. 2021Hallucination Improves Few-Shot Object Detectioncited by 50
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 11; 2023: 21; 2024: 14; 2025: 13; 2026: 5.

64 papers.

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  1. 2023Multi-modal Queried Object Detection in the Wildcited by 47
  2. 2024Cross-Domain Few-Shot Object Detection via Enhanced Open-Set Object Detectorcited by 43
  3. 2023Explore the Power of Synthetic Data on Few-shot Object Detectioncited by 38
  4. 2023Vision Transformer Off-the-Shelf: A Surprising Baseline for Few-Shot Class-Agnostic Countingcited by 25
  5. 2023Supervised Masked Knowledge Distillation for Few-Shot Transformerscited by 23
  6. 2023Machine Learning for Autonomous Vehicle's Trajectory Prediction: A comprehensive survey, Challenges, and Future Research Directionscited by 23
  7. 2024MoDE: CLIP Data Experts via Clusteringcited by 22
  8. 2023DiGeo: Discriminative Geometry-Aware Learning for Generalized Few-Shot Object Detectioncited by 21
  9. 2023Generating Features with Increased Crop-related Diversity for Few-Shot Object Detectioncited by 21
  10. 2022FS-DETR: Few-Shot DEtection TRansformer with prompting and without re-trainingcited by 20
  11. 2022Few-Shot Learning Meets Transformer: Unified Query-Support Transformers for Few-Shot Classificationcited by 16
  12. 2023Detect Everything with Few Examplescited by 14
38 more
  1. 2022Disentangle and Remerge: Interventional Knowledge Distillation for Few-Shot Object Detection from A Conditional Causal Perspectivecited by 13
  2. 2022Breaking Immutable: Information-Coupled Prototype Elaboration for Few-Shot Object Detectioncited by 12
  3. 2023Reference Twice: A Simple and Unified Baseline for Few-Shot Instance Segmentationcited by 12
  4. 2022Multi-Modal Few-Shot Object Detection with Meta-Learning-Based Cross-Modal Promptingcited by 11
  5. 2024Fine-Grained Prototypes Distillation for Few-Shot Object Detectioncited by 10
  6. 2024AirShot: Efficient Few-Shot Detection for Autonomous Explorationcited by 10
  7. 2022Integrally Migrating Pre-trained Transformer Encoder-decoders for Visual Object Detectioncited by 9
  8. 2025No time to train! Training-Free Reference-Based Instance Segmentationcited by 9
  9. 2022Hierarchical Few-Shot Object Detection: Problem, Benchmark and Methodcited by 8
  10. 2023FER-former: Multi-modal Transformer for Facial Expression Recognitioncited by 8
  11. 2024SMILe: Leveraging Submodular Mutual Information For Robust Few-Shot Object Detectioncited by 8
  12. 2025Fine-Grained Zero-Shot Object Detectioncited by 8
  13. 2023Identification of Novel Classes for Improving Few-Shot Object Detectioncited by 7
  14. 2022Hierarchical Attention Network for Few-Shot Object Detection via Meta-Contrastive Learningcited by 6
  15. 2024Chameleon: A Data-Efficient Generalist for Dense Visual Prediction in the Wildcited by 6
  16. 2024Learning Unknowns from Unknowns: Diversified Negative Prototypes Generator for Few-Shot Open-Set Recognitioncited by 6
  17. 2025Multi-Perspective Data Augmentation for Few-shot Object Detectioncited by 6
  18. 2025Generalized Semantic Contrastive Learning via Embedding Side Information for Few-Shot Object Detectioncited by 6
  19. 2025Visual Textualization for Image Prompted Object Detectioncited by 6
  20. 2023The Art of Camouflage: Few-Shot Learning for Animal Detection and Segmentationcited by 5
  21. 2023Improved Region Proposal Network for Enhanced Few-Shot Object Detectioncited by 5
  22. 2024Cross-domain Multi-modal Few-shot Object Detection via Rich Textcited by 5
  23. 2024Search and Detect: Training-Free Long Tail Object Detection via Web-Image Retrievalcited by 5
  24. 2022Enhancing Few-shot Image Classification with Cosine Transformercited by 4
  25. 2023Meta-tuning Loss Functions and Data Augmentation for Few-shot Object Detectioncited by 4
  26. 2023ECEA: Extensible Co-Existing Attention for Few-Shot Object Detectioncited by 4
  27. 2025CDFormer: Cross-Domain Few-Shot Object Detection Transformer Against Feature Confusioncited by 4
  28. 2025Decoupling Template Bias in CLIP: Harnessing Empty Prompts for Enhanced Few-Shot Learningcited by 4
  29. 2023An Effective Crop-Paste Pipeline for Few-shot Object Detectioncited by 3
  30. 2023Few-Shot Object Detection via Synthetic Features with Optimal Transportcited by 3
  31. 2026Learning Multi-Modal Prototypes for Cross-Domain Few-Shot Object Detectioncited by 3
  32. 2022Proposal Distribution Calibration for Few-Shot Object Detectioncited by 2
  33. 2023TIDE: Test Time Few Shot Object Detectioncited by 2
  34. 2024UniFS: Universal Few-shot Instance Perception with Point Representationscited by 2
  35. 2025Few-Shot Learning in Video and 3D Object Detection: A Surveycited by 2
  36. 2026FSOD-VFM: Few-Shot Object Detection with Vision Foundation Models and Graph Diffusioncited by 2
  37. 2022A Comparative Attention Framework for Better Few-Shot Object Detection on Aerial Imagescited by 1
  38. 2023Decoupled DETR For Few-shot Object Detectioncited by 1

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