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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 8190 of 188 papers

TitleStatusHype
Do Vision-and-Language Transformers Learn Grounded Predicate-Noun Dependencies?Code0
Align before Search: Aligning Ads Image to Text for Accurate Cross-Modal Sponsored SearchCode0
Dissecting Deep Metric Learning Losses for Image-Text RetrievalCode0
Position Focused Attention Network for Image-Text MatchingCode0
Towards Better Multi-modal Keyphrase Generation via Visual Entity Enhancement and Multi-granularity Image Noise FilteringCode0
Beyond Image-Text Matching: Verb Understanding in Multimodal Transformers Using Guided MaskingCode0
Deep Cross-Modal Projection Learning for Image-Text MatchingCode0
Integrating Language Guidance Into Image-Text Matching for Correcting False NegativesCode0
Backdoor Attack on Unpaired Medical Image-Text Foundation Models: A Pilot Study on MedCLIPCode0
Increasing Textual Context Size Boosts Medical Image-Text MatchingCode0
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