mlsanityData to 7 Oct 2026

Recent Advance in Content-based Image Retrieval: A Literature Survey

arXiv 1706.06064 ↗First posted 19 Jun 2017cs.MM cs.IRcited by 24

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Abstract (arXiv)

The explosive increase and ubiquitous accessibility of visual data on the Web have led to the prosperity of research activity in image search or retrieval. With the ignorance of visual content as a ranking clue, methods with text search techniques for visual retrieval may suffer inconsistency between the text words and visual content. Content-based image retrieval (CBIR), which makes use of the representation of visual content to identify relevant images, has attracted sustained attention in recent two decades. Such a problem is challenging due to the intention gap and the semantic gap problems. Numerous techniques have been developed for content-based image retrieval in the last decade. The purpose of this paper is to categorize and evaluate those algorithms proposed during the period of 2003 to 2016. We conclude with several promising directions for future research.

Key facts. Cited by 24 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Jun 2017.

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Citing papers per year: 2021: 8; 2022: 1; 2023: 5; 2024: 8; 2025: 1; 2026: 1.

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  1. 2023Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Taskscited by 72
  2. 2021Deep Learning for Instance Retrieval: A Surveycited by 70
  3. 2021DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Featurescited by 54
  4. 2024Enhancing Interactive Image Retrieval With Query Rewriting Using Large Language Models and Vision Language Modelscited by 19
  5. 2023IRGen: Generative Modeling for Image Retrievalcited by 18
  6. 2021Neural ranking models for document retrievalcited by 16
  7. 2021Telling the What while Pointing to the Where: Multimodal Queries for Image Retrievalcited by 12
  8. 2021Deep Triplet Hashing Network for Case-based Medical Image Retrievalcited by 8
  9. 2026Unlocking Multimodal Document Intelligence: From Current Triumphs to Future Frontiers of Visual Document Retrievalcited by 8
  10. 2024Zero-shot Composed Image Retrieval Considering Query-target Relationship Leveraging Masked Image-text Pairscited by 7
  11. 2022DALG: Deep Attentive Local and Global Modeling for Image Retrievalcited by 6
  12. 2023Leveraging BEV Representation for 360-degree Visual Place Recognitioncited by 4
12 more
  1. 2024Towards Cross-modal Backward-compatible Representation Learning for Vision-Language Modelscited by 4
  2. 2021Searching for Pneumothorax in X-Ray Images Using Autoencoded Deep Featurescited by 2
  3. 2024Supporting Experts with a Multimodal Machine-Learning-Based Tool for Human Behavior Analysis of Conversational Videoscited by 2
  4. 2025DORAEMON: A Unified Library for Visual Object Modeling and Representation Learning at Scalecited by 2
  5. 2021Ghost-dil-NetVLAD: A Lightweight Neural Network for Visual Place Recognitioncited by 1
  6. 2023Rank Flow Embedding for Unsupervised and Semi-Supervised Manifold Learningcited by 1
  7. 2024Visual Navigation of Digital Libraries: Retrieval and Classification of Images in the National Library of Norway's Digitised Book Collectioncited by 1
  8. 2021PrivateMail: Supervised Manifold Learning of Deep Features With Differential Privacy for Image Retrievalcited by 0
  9. 2023Pattern retrieval of traffic congestion using graph-based associations of traffic domain-specific featurescited by 0
  10. 2024MARs: Multi-view Attention Regularizations for Patch-based Feature Recognition of Space Terraincited by 0
  11. 2024Self-supervised cross-modality learning for uncertainty-aware object detection and recognition in applications which lack pre-labelled training datacited by 0
  12. 2024Enhancing Visual Re-ranking through Denoising Nearest Neighbor Graph via Continuous CRFcited by 0