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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 131140 of 188 papers

TitleStatusHype
Probing the Role of Positional Information in Vision-Language Models0
Negative-Aware Attention Framework for Image-Text MatchingCode1
Unified Multimodal Pre-training and Prompt-based Tuning for Vision-Language Understanding and Generation0
Embedding Arithmetic of Multimodal Queries for Image Retrieval0
DenseCLIP: Language-Guided Dense Prediction with Context-Aware PromptingCode1
Learning with Noisy Correspondence for Cross-modal MatchingCode1
UFO: A UniFied TransfOrmer for Vision-Language Representation Learning0
More Than Just Attention: Improving Cross-Modal Attentions with Contrastive Constraints for Image-Text Matching0
MURAL: Multimodal, Multitask Representations Across Languages0
Is An Image Worth Five Sentences? A New Look into Semantics for Image-Text Matching0
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