mlsanityData to 14 Oct 2026

Breaking Immutable: Information-Coupled Prototype Elaboration for Few-Shot Object Detection

arXiv 2211.14782 ↗First posted 27 Nov 2022cs.CVcited by 12

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Abstract (arXiv)

Few-shot object detection, expecting detectors to detect novel classes with a few instances, has made conspicuous progress. However, the prototypes extracted by existing meta-learning based methods still suffer from insufficient representative information and lack awareness of query images, which cannot be adaptively tailored to different query images. Firstly, only the support images are involved for extracting prototypes, resulting in scarce perceptual information of query images. Secondly, all pixels of all support images are treated equally when aggregating features into prototype vectors, thus the salient objects are overwhelmed by the cluttered background. In this paper, we propose an Information-Coupled Prototype Elaboration (ICPE) method to generate specific and representative prototypes for each query image. Concretely, a conditional information coupling module is introduced to couple information from the query branch to the support branch, strengthening the query-perceptual information in support features. Besides, we design a prototype dynamic aggregation module that dynamically adjusts intra-image and inter-image aggregation weights to highlight the salient information useful for detecting query images. Experimental results on both Pascal VOC and MS COCO demonstrate that our method achieves state-of-the-art performance in almost all settings.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 45 of its 55 references that are in the map. First posted on arXiv 27 Nov 2022.

Builds on

45 of 55 references.

References · 45

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33 more
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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 5; 2025: 3; 2026: 3.

12 papers.

  1. 2024Adapting Pre-Trained Vision Models for Novel Instance Detection and Segmentationcited by 17
  2. 2025Domain-RAG: Retrieval-Guided Compositional Image Generation for Cross-Domain Few-Shot Object Detectioncited by 15
  3. 2024Commonsense Prototype for Outdoor Unsupervised 3D Object Detectioncited by 13
  4. 2024Few-Shot Object Detection: Research Advances and Challengescited by 11
  5. 2025Visual Textualization for Image Prompted Object Detectioncited by 6
  6. 2024BIV-Priv-Seg: Locating Private Content in Images Taken by People With Visual Impairmentscited by 5
  7. 2025Generalization-Enhanced Few-Shot Object Detection in Remote Sensingcited by 4
  8. 2023Few-Shot Object Detection via Synthetic Features with Optimal Transportcited by 3
  9. 2026Learning Multi-Modal Prototypes for Cross-Domain Few-Shot Object Detectioncited by 3
  10. 2024PS-TTL: Prototype-based Soft-labels and Test-Time Learning for Few-shot Object Detectioncited by 2
  11. 2026Prototype Memory-Guided Training-Free Anomaly Classification and Localization in Prenatal Ultrasoundcited by 1
  12. 2026Unified Unsupervised and Sparsely-Supervised 3D Object Detection by Semantic Pseudo-Labeling and Prototype Learningcited by 0