mlsanityData to 7 Oct 2026

Deep Randomized Ensembles for Metric Learning

arXiv 1808.04469 ↗First posted 13 Aug 2018cs.CVcited by 17

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Abstract (arXiv)

Learning embedding functions, which map semantically related inputs to nearby locations in a feature space supports a variety of classification and information retrieval tasks. In this work, we propose a novel, generalizable and fast method to define a family of embedding functions that can be used as an ensemble to give improved results. Each embedding function is learned by randomly bagging the training labels into small subsets. We show experimentally that these embedding ensembles create effective embedding functions. The ensemble output defines a metric space that improves state of the art performance for image retrieval on CUB-200-2011, Cars-196, In-Shop Clothes Retrieval and VehicleID.

Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Aug 2018.

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Citing papers per year: 2021: 9; 2022: 5; 2023: 2; 2024: 1.

17 papers.

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  1. 2021Deep Learning for Instance Retrieval: A Surveycited by 70
  2. 2021Learning Intra-Batch Connections for Deep Metric Learningcited by 34
  3. 2021Towards Interpretable Deep Metric Learning with Structural Matchingcited by 30
  4. 2021Deep Relational Metric Learningcited by 22
  5. 2022Integrating Language Guidance into Vision-based Deep Metric Learningcited by 19
  6. 2022Verification-Aided Deep Ensemble Selectioncited by 18
  7. 2021Informative and Representative Triplet Selection for Multilabel Remote Sensing Image Retrievalcited by 9
  8. 2022Contrastive Bayesian Analysis for Deep Metric Learningcited by 8
  9. 2023Introspective Deep Metric Learningcited by 7
  10. 2024Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentationcited by 7
  11. 2021Improving Deep Metric Learning by Divide and Conquercited by 5
  12. 2021Atlas Based Representation and Metric Learning on Manifoldscited by 3
5 more
  1. 2022Deep Metric Learning with Chance Constraintscited by 3
  2. 2023Generalized Sum Pooling for Metric Learningcited by 1
  3. 2021Open-Set Representation Learning through Combinatorial Embeddingcited by 0
  4. 2021CBIR using Pre-Trained Neural Networkscited by 0
  5. 2022Introspective Deep Metric Learning for Image Retrievalcited by 0