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Image-text matching

Image-Text Matching is a subtask within Cross-Modal Retrieval (CMR) that involves establishing associations between images and corresponding textual descriptions. The goal is to retrieve an image given a textual query or, conversely, retrieve a textual description given an image query. This task is challenging due to the heterogeneity gap between image and text data representations. Image-text matching is used in applications such as content-based image search, visual question answering, and multimodal summarization.

Assessing Brittleness of Image-Text Retrieval Benchmarks from Vision-Language Models Perspective

Papers

Showing 5160 of 188 papers

TitleStatusHype
CCMB: A Large-scale Chinese Cross-modal BenchmarkCode1
Declaration-based Prompt Tuning for Visual Question AnsweringCode1
No Token Left Behind: Explainability-Aided Image Classification and GenerationCode1
ECCV Caption: Correcting False Negatives by Collecting Machine-and-Human-verified Image-Caption Associations for MS-COCOCode1
MVPTR: Multi-Level Semantic Alignment for Vision-Language Pre-Training via Multi-Stage LearningCode1
Negative-Aware Attention Framework for Image-Text MatchingCode1
DenseCLIP: Language-Guided Dense Prediction with Context-Aware PromptingCode1
Learning with Noisy Correspondence for Cross-modal MatchingCode1
Align before Fuse: Vision and Language Representation Learning with Momentum DistillationCode1
A Deep Local and Global Scene-Graph Matching for Image-Text RetrievalCode1
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