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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 171180 of 188 papers

TitleStatusHype
Enhancing Image-Text Matching with Adaptive Feature AggregationCode0
RoCOCO: Robustness Benchmark of MS-COCO to Stress-test Image-Text Matching ModelsCode0
Align before Search: Aligning Ads Image to Text for Accurate Cross-Modal Sponsored SearchCode0
ALADIN: Distilling Fine-grained Alignment Scores for Efficient Image-Text Matching and RetrievalCode0
Learning fragment self-attention embeddings for image-text matchingCode0
Integrating Language Guidance Into Image-Text Matching for Correcting False NegativesCode0
Increasing Textual Context Size Boosts Medical Image-Text MatchingCode0
Dissecting Deep Metric Learning Losses for Image-Text RetrievalCode0
Improving Multimodal Classification of Social Media Posts by Leveraging Image-Text Auxiliary TasksCode0
Vision Meets Definitions: Unsupervised Visual Word Sense Disambiguation Incorporating Gloss InformationCode0
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