mlsanityData to 7 Oct 2026

ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis

arXiv 2004.01113 ↗First posted 2 Apr 2020cs.CVcited by 107

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Abstract (arXiv)

We consider the problem of distance metric learning (DML), where the task is to learn an effective similarity measure between images. We revisit ProxyNCA and incorporate several enhancements. We find that low temperature scaling is a performance-critical component and explain why it works. Besides, we also discover that Global Max Pooling works better in general when compared to Global Average Pooling. Additionally, our proposed fast moving proxies also addresses small gradient issue of proxies, and this component synergizes well with low temperature scaling and Global Max Pooling. Our enhanced model, called ProxyNCA++, achieves a 22.9 percentage point average improvement of Recall@1 across four different zero-shot retrieval datasets compared to the original ProxyNCA algorithm. Furthermore, we achieve state-of-the-art results on the CUB200, Cars196, Sop, and InShop datasets, achieving Recall@1 scores of 72.2, 90.1, 81.4, and 90.9, respectively.

Key facts. Cited by 107 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Apr 2020.

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Citing papers per year: 2021: 19; 2022: 27; 2023: 22; 2024: 17; 2025: 13; 2026: 9.

107 papers.

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  1. 2021ABO: Dataset and Benchmarks for Real-World 3D Object Understandingcited by 360
  2. 2022How to Exploit Hyperspherical Embeddings for Out-of-Distribution Detection?cited by 128
  3. 2022Hyperbolic Vision Transformers: Combining Improvements in Metric Learningcited by 109
  4. 2021Training Vision Transformers for Image Retrievalcited by 90
  5. 2021Recall@k Surrogate Loss with Large Batches and Similarity Mixupcited by 49
  6. 2021von Mises-Fisher Loss: An Exploration of Embedding Geometries for Supervised Learningcited by 42
  7. 2021Learning Intra-Batch Connections for Deep Metric Learningcited by 34
  8. 2022Non-isotropy Regularization for Proxy-based Deep Metric Learningcited by 33
  9. 2023Probabilistic Contrastive Learning Recovers the Correct Aleatoric Uncertainty of Ambiguous Inputscited by 28
  10. 2022HIER: Metric Learning Beyond Class Labels via Hierarchical Regularizationcited by 26
  11. 2021Noise-resistant Deep Metric Learning with Ranking-based Instance Selectioncited by 23
  12. 2021It Takes Two to Tango: Mixup for Deep Metric Learningcited by 23
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  1. 2021Robust and Decomposable Average Precision for Image Retrievalcited by 19
  2. 2022Integrating Language Guidance into Vision-based Deep Metric Learningcited by 19
  3. 2022A Non-isotropic Probabilistic Take on Proxy-based Deep Metric Learningcited by 19
  4. 2021Hierarchical Proxy-based Loss for Deep Metric Learningcited by 18
  5. 2023ERM++: An Improved Baseline for Domain Generalizationcited by 18
  6. 2023CHAMMI: A benchmark for channel-adaptive models in microscopy imagingcited by 18
  7. 2021Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learningcited by 17
  8. 2022Continual Learning for Visual Search with Backward Consistent Feature Embeddingcited by 17
  9. 2025DA-VPT: Semantic-Guided Visual Prompt Tuning for Vision Transformerscited by 17
  10. 2023Proxy Anchor-based Unsupervised Learning for Continuous Generalized Category Discoverycited by 16
  11. 2023Open Set Synthetic Image Source Attributioncited by 12
  12. 2022Fine-grained Retrieval Prompt Tuningcited by 11
  13. 2023Optimization of Rank Losses for Image Retrievalcited by 10
  14. 2024Understanding Hyperbolic Metric Learning through Hard Negative Samplingcited by 10
  15. 2024Enhancing Feature Diversity Boosts Channel-Adaptive Vision Transformerscited by 10
  16. 2024Bringing Multimodality to Amazon Visual Search Systemcited by 10
  17. 2021Effectively Leveraging Attributes for Visual Similaritycited by 9
  18. 2022Spectral, Probabilistic, and Deep Metric Learning: Tutorial and Surveycited by 9
  19. 2024Towards Improved Proxy-based Deep Metric Learning via Data-Augmented Domain Adaptationcited by 9
  20. 2022Hierarchical Average Precision Training for Pertinent Image Retrievalcited by 8
  21. 2022Contrastive Bayesian Analysis for Deep Metric Learningcited by 8
  22. 2023Threshold-Consistent Margin Loss for Open-World Deep Metric Learningcited by 7
  23. 2023Introspective Deep Metric Learningcited by 7
  24. 2024Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentationcited by 7
  25. 2022The Group Loss++: A deeper look into group loss for deep metric learningcited by 6
  26. 2024Learning Semantic Proxies from Visual Prompts for Parameter-Efficient Fine-Tuning in Deep Metric Learningcited by 6
  27. 2024DVF: Advancing Robust and Accurate Fine-Grained Image Retrieval with Retrieval Guidelinescited by 6
  28. 2025ChA-MAEViT: Unifying Channel-Aware Masked Autoencoders and Multi-Channel Vision Transformers for Improved Cross-Channel Learningcited by 6
  29. 2025Multi-modal Reference Learning for Fine-grained Text-to-Image Retrievalcited by 6
  30. 2022DAS: Densely-Anchored Sampling for Deep Metric Learningcited by 5
  31. 2022Supervised Metric Learning to Rank for Retrieval via Contextual Similarity Optimizationcited by 5
  32. 2024Globally Correlation-Aware Hard Negative Generationcited by 5
  33. 2025Isolated Channel Vision Transformers: From Single-Channel Pretraining to Multi-Channel Finetuningcited by 5
  34. 2025LOCORE: Image Re-ranking with Long-Context Sequence Modelingcited by 5
  35. 2021Rethinking the Optimization of Average Precision: Only Penalizing Negative Instances before Positive Ones is Enoughcited by 4
  36. 2021Multi-Head Deep Metric Learning Using Global and Local Representationscited by 4
  37. 2022Large-to-small Image Resolution Asymmetry in Deep Metric Learningcited by 4
  38. 2022Self-Supervised 3D Traversability Estimation with Proxy Bank Guidancecited by 4

50 most cited of 107 All 107 (JSON)