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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 91100 of 188 papers

TitleStatusHype
Efficient and Long-Tailed Generalization for Pre-trained Vision-Language ModelCode0
Improving Multimodal Classification of Social Media Posts by Leveraging Image-Text Auxiliary TasksCode0
Increasing Textual Context Size Boosts Medical Image-Text MatchingCode0
Align before Search: Aligning Ads Image to Text for Accurate Cross-Modal Sponsored SearchCode0
Matching Images and Text with Multi-modal Tensor Fusion and Re-rankingCode0
Towards Better Multi-modal Keyphrase Generation via Visual Entity Enhancement and Multi-granularity Image Noise FilteringCode0
Enhancing Image-Text Matching with Adaptive Feature AggregationCode0
ALADIN: Distilling Fine-grained Alignment Scores for Efficient Image-Text Matching and RetrievalCode0
Evaluating Attribute Comprehension in Large Vision-Language ModelsCode0
MAGID: An Automated Pipeline for Generating Synthetic Multi-modal DatasetsCode0
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