mlsanityData to 14 Oct 2026

Visual Instance Retrieval with Deep Convolutional Networks

arXiv 1412.6574 ↗First posted 20 Dec 2014cs.CVcited by 48

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Abstract (arXiv)

This paper provides an extensive study on the availability of image representations based on convolutional networks (ConvNets) for the task of visual instance retrieval. Besides the choice of convolutional layers, we present an efficient pipeline exploiting multi-scale schemes to extract local features, in particular, by taking geometric invariance into explicit account, i.e. positions, scales and spatial consistency. In our experiments using five standard image retrieval datasets, we demonstrate that generic ConvNet image representations can outperform other state-of-the-art methods if they are extracted appropriately.

Key facts. Cited by 48 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 Dec 2014.

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Citing papers per year: 2021: 8; 2022: 14; 2023: 15; 2024: 4; 2025: 6; 2026: 1.

48 papers.

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  1. 2022Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Modelscited by 424
  2. 2023AnyLoc: Towards Universal Visual Place Recognitioncited by 163
  3. 2023EigenPlaces: Training Viewpoint Robust Models for Visual Place Recognitioncited by 111
  4. 2022Deep Visual Geo-localization Benchmarkcited by 84
  5. 2021Deep Learning for Instance Retrieval: A Surveycited by 70
  6. 2021The 2021 Image Similarity Dataset and Challengecited by 44
  7. 2023Global Features are All You Need for Image Retrieval and Rerankingcited by 41
  8. 2025ILIAS: Instance-Level Image retrieval At Scalecited by 30
  9. 2022Investigating the Role of Image Retrieval for Visual Localization -- An exhaustive benchmarkcited by 27
  10. 2021Compatibility-aware Heterogeneous Visual Searchcited by 23
  11. 2021Semantic Reinforced Attention Learning for Visual Place Recognitioncited by 19
  12. 2023IRGen: Generative Modeling for Image Retrievalcited by 18
36 more
  1. 2021All the attention you need: Global-local, spatial-channel attention for image retrievalcited by 12
  2. 2021Investigating the Vision Transformer Model for Image Retrieval Taskscited by 11
  3. 2023Design Space Exploration of Low-Bit Quantized Neural Networks for Visual Place Recognitioncited by 11
  4. 2025Scaling Image Geo-Localization to Continent Levelcited by 10
  5. 2024MeshVPR: Citywide Visual Place Recognition Using 3D Meshescited by 8
  6. 2023DINO-Mix: Enhancing Visual Place Recognition with Foundational Vision Model and Feature Mixingcited by 7
  7. 2021ES-Net: Erasing Salient Parts to Learn More in Re-Identificationcited by 6
  8. 2022Semantic Pose Verification for Outdoor Visual Localization with Self-supervised Contrastive Learningcited by 5
  9. 2022Condition-Invariant and Compact Visual Place Description by Convolutional Autoencodercited by 5
  10. 2022NORPPA: NOvel Ringed seal re-identification by Pelage Pattern Aggregationcited by 5
  11. 2023Towards Content-based Pixel Retrieval in Revisited Oxford and Pariscited by 5
  12. 2025LOCORE: Image Re-ranking with Long-Context Sequence Modelingcited by 5
  13. 2022Group Generalized Mean Pooling for Vision Transformercited by 4
  14. 2023VG-SSL: Benchmarking Self-supervised Representation Learning Approaches for Visual Geo-localizationcited by 4
  15. 2022Medical Image Retrieval via Nearest Neighbor Search on Pre-trained Image Featurescited by 3
  16. 2023Efficient Discovery and Effective Evaluation of Visual Perceptual Similarity: A Benchmark and Beyondcited by 3
  17. 2024On Train-Test Class Overlap and Detection for Image Retrievalcited by 3
  18. 2025To Match or Not to Match: Revisiting Image Matching for Reliable Visual Place Recognitioncited by 3
  19. 2021Image Collation: Matching illustrations in manuscriptscited by 2
  20. 2023Asymmetric Image Retrieval with Cross Model Compatible Ensemblescited by 2
  21. 2023Divide&Classify: Fine-Grained Classification for City-Wide Visual Place Recognitioncited by 2
  22. 2024Collaborative Visual Place Recognition through Federated Learningcited by 2
  23. 2025Patch-wise Retrieval: A Bag of Practical Techniques for Instance-level Matchingcited by 2
  24. 2022Topological structure of complex predictionscited by 1
  25. 2022Instance Image Retrieval by Learning Purely From Within the Datasetcited by 1
  26. 2023Rank Flow Embedding for Unsupervised and Semi-Supervised Manifold Learningcited by 1
  27. 2024Relational Self-supervised Distillation with Compact Descriptors for Image Copy Detectioncited by 1
  28. 2025Find your Needle: Small Object Image Retrieval via Multi-Object Attention Optimizationcited by 1
  29. 2026ELViS: Efficient Visual Similarity from Local Descriptors that Generalizes Across Domainscited by 1
  30. 2022Indicative Image Retrieval: Turning Blackbox Learning into Greycited by 0
  31. 2022U(1) Symmetry-breaking Observed in Generic CNN Bottleneck Layerscited by 0
  32. 2022Object-Level Targeted Selection via Deep Template Matchingcited by 0
  33. 2022Learning Deep Representations via Contrastive Learning for Instance Retrievalcited by 0
  34. 2023MABNet: Master Assistant Buddy Network with Hybrid Learning for Image Retrievalcited by 0
  35. 2023A Triplet-loss Dilated Residual Network for High-Resolution Representation Learning in Image Retrievalcited by 0
  36. 2023Coloring Deep CNN Layers with Activation Hue Losscited by 0