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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 101110 of 188 papers

TitleStatusHype
Advanced Multimodal Deep Learning Architecture for Image-Text Matching0
Hire: Hybrid-modal Interaction with Multiple Relational Enhancements for Image-Text Matching0
DEMO: A Statistical Perspective for Efficient Image-Text Matching0
CLIP-Powered TASS: Target-Aware Single-Stream Network for Audio-Visual Question Answering0
RETTA: Retrieval-Enhanced Test-Time Adaptation for Zero-Shot Video Captioning0
Breaking Through the Noisy Correspondence: A Robust Model for Image-Text Matching0
SyncMask: Synchronized Attentional Masking for Fashion-centric Vision-Language Pretraining0
Constructing Multilingual Visual-Text Datasets Revealing Visual Multilingual Ability of Vision Language Models0
FSMR: A Feature Swapping Multi-modal Reasoning Approach with Joint Textual and Visual Clues0
MAGID: An Automated Pipeline for Generating Synthetic Multi-modal DatasetsCode0
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