Image-Text Retrieval

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Overview

Image-text retrieval studies how to find relevant images from text queries and relevant text from images, making large visual collections searchable in natural language. Many systems use CLIP-style dual encoders trained with contrastive learning to place images and text in a shared embedding space, while region-token alignment and reranking improve fine-grained matches. Benchmarks such as MSCOCO and Flickr30K test general caption retrieval, alongside domain-specific settings including radiology, remote sensing, fashion, and person search. A central challenge is moving beyond clean, short paired captions to handle long or compositional queries, noisy matches, subtle visual details, and shifts between training and deployment domains.

Latest papers

CardsList

38 papers4 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

  1. Camouflage-aware Image-Text Retrieval via Expert Collaboration

    Apr 1, 2026Yao Jiang, Zhongkuan Mao, Xuan Wu +2Image-Text RetrievalCross-Modal Retrieval

    College of Computer Science, Sichuan University · National Key Lab of Fundamental Science on Synthetic Vision, Sichuan University

  2. Robust Remote Sensing Image-Text Retrieval with Noisy Correspondence

    Mar 30, 2026Qiya Song, Yiqiang Xie, Yuan Sun +2Image-Text RetrievalRetrieval Robustness

    Hunan Normal University, Changsha, China 410081 · Sichuan University, Chengdu, China 610044 · Hunan University, Changsha, China 410082

  3. Brain-Inspired Multimodal Spiking Neural Network for Image-Text Retrieval

    Mar 25, 2026Xintao Zong, Xian Zhong, Wenxuan Liu +3Image-Text RetrievalSpiking Neural Networks

    Hubei Key Laboratory of Transportation Internet of Things, Wuhan University of Technology · State Key Laboratory for Multimedia Information Processing, Peking University

  4. Cross-modal Fuzzy Alignment Network for Text-Aerial Person Retrieval and A Large-scale Benchmark

    Mar 21, 2026Yifei Deng, Chenglong Li, Yuyang Zhang +2Image-Text RetrievalCross-Modal Alignment

    State Key Laboratory of Opto-Electronic Information Acquisition and Protection Technology · School of Computer Science and Technology, Anhui University · The University of Hong Kong +1

  5. Grounded Multimodal Retrieval-Augmented Drafting of Radiology Impressions Using Case-Based Similarity Search

    Mar 18, 2026Himadri S SamantaRadiology Report GenerationMultimodal RAG

    Independent AI Researcher, Austin, Texas, USA

  6. CLIP Is Shortsighted: Paying Attention Beyond the First Sentence

    Feb 25, 2026Marc-Antoine Lavoie, Anas Mahmoud, Aldo Zaimi +2Position Bias in VLMsVision-Language Alignment

    University of Toronto Robotics Institute · Mila - Quebec AI Institute

  7. MedProbCLIP: Probabilistic Adaptation of Vision-Language Foundation Model for Reliable Radiograph-Report Retrieval

    Feb 17, 2026Ahmad Elallaf, Yu Zhang, Yuktha Priya Masupalli +4Radiology VLMsVision-Language Models

    Texas A&M University-San Antonio · Boise State University

  8. Accurate and Scalable Multimodal Pathology Retrieval via Attentive Vision-Language Alignment

    Oct 27, 2025Hongyi Wang, Zhengjie Zhu, Junlin Hou +13Multimodal IRComputational Pathology

    Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China · College of Computer Science and Technology, Zhejiang University, Hangzhou, China. · School of Medicine, Wake Forest University, Winston-Salem, NC, USA. +11