mlsanityData to 7 Oct 2026

DMN4: Few-shot Learning via Discriminative Mutual Nearest Neighbor Neural Network

arXiv 2103.08160 ↗First posted 15 Mar 2021cs.CV cs.LGcited by 9

Not on the map. Why?

Abstract (arXiv)

Few-shot learning (FSL) aims to classify images under low-data regimes, where the conventional pooled global feature is likely to lose useful local characteristics. Recent work has achieved promising performances by using deep descriptors. They generally take all deep descriptors from neural networks into consideration while ignoring that some of them are useless in classification due to their limited receptive field, e.g., task-irrelevant descriptors could be misleading and multiple aggregative descriptors from background clutter could even overwhelm the object's presence. In this paper, we argue that a Mutual Nearest Neighbor (MNN) relation should be established to explicitly select the query descriptors that are most relevant to each task and discard less relevant ones from aggregative clutters in FSL. Specifically, we propose Discriminative Mutual Nearest Neighbor Neural Network (DMN4) for FSL. Extensive experiments demonstrate that our method outperforms the existing state-of-the-arts on both fine-grained and generalized datasets.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 31 of its 46 references that are in the map. First posted on arXiv 15 Mar 2021.

Builds on

31 of 46 references.

References · 31

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19 more
  1. 2017Few-Shot Learning with Graph Neural Networkscited by 324
  2. 2018Meta-Transfer Learning for Few-Shot Learningcited by 306
  3. 2018Few-Shot Learning via Embedding Adaptation with Set-to-Set Functionscited by 293
  4. 2017Meta Networkscited by 268
  5. 2018Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learningcited by 208
  6. 2020CrossTransformers: spatially-aware few-shot transfercited by 174
  7. 2020Negative Margin Matters: Understanding Margin in Few-shot Classificationcited by 129
  8. 2017Few-Shot Image Recognition by Predicting Parameters from Activationscited by 122
  9. 2019Revisiting Local Descriptor based Image-to-Class Measure for Few-shot Learningcited by 121
  10. 2020Few-Shot Classification with Feature Map Reconstruction Networkscited by 116
  11. 2019TapNet: Neural Network Augmented with Task-Adaptive Projection for Few-Shot Learningcited by 90
  12. 2019Generating Classification Weights with GNN Denoising Autoencoders for Few-Shot Learningcited by 69
  13. 2018Memory Matching Networks for One-Shot Image Recognitioncited by 65
  14. 2019Associative Alignment for Few-shot Image Classificationcited by 58
  15. 2019Few-Shot Learning with Embedded Class Models and Shot-Free Meta Trainingcited by 57
  16. 2019Dense Classification and Implanting for Few-Shot Learningcited by 56
  17. 2018Few-Shot Learning with Metric-Agnostic Conditional Embeddingscited by 40
  18. 2019An Ensemble of Epoch-wise Empirical Bayes for Few-shot Learningcited by 38
  19. 2019Few-Shot Learning with Localization in Realistic Settingscited by 34

Built on by

Cited by year

Citing papers per year: 2021: 2; 2022: 2; 2023: 4; 2024: 1.

9 papers.

  1. 2022Boosting Few-shot Fine-grained Recognition with Background Suppression and Foreground Alignmentcited by 29
  2. 2021Learning to Affiliate: Mutual Centralized Learning for Few-shot Classificationcited by 18
  3. 2021Sparse Spatial Transformers for Few-Shot Learningcited by 14
  4. 2022RankDNN: Learning to Rank for Few-shot Learningcited by 7
  5. 2023PrototypeFormer: Learning to Explore Prototype Relationships for Few-shot Image Classificationcited by 3
  6. 2023TALDS-Net: Task-Aware Adaptive Local Descriptors Selection for Few-shot Image Classificationcited by 2
  7. 2023P3DC-Shot: Prior-Driven Discrete Data Calibration for Nearest-Neighbor Few-Shot Classificationcited by 1
  8. 2023Recent Advances of Local Mechanisms in Computer Vision: A Survey and Outlook of Recent Workcited by 0
  9. 2024A Simple Task-aware Contrastive Local Descriptor Selection Strategy for Few-shot Learning between inter class and intra classcited by 0