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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 6170 of 188 papers

TitleStatusHype
Learning Comprehensive Representations with Richer Self for Text-to-Image Person Re-Identification0
Prototype-based Aleatoric Uncertainty Quantification for Cross-modal RetrievalCode1
Align before Search: Aligning Ads Image to Text for Accurate Cross-Modal Sponsored SearchCode0
Dynamic Visual Semantic Sub-Embeddings and Fast Re-Ranking0
Improving Multimodal Classification of Social Media Posts by Leveraging Image-Text Auxiliary TasksCode0
Towards Better Multi-modal Keyphrase Generation via Visual Entity Enhancement and Multi-granularity Image Noise FilteringCode0
ViLTA: Enhancing Vision-Language Pre-training through Textual Augmentation0
Uniformly Distributed Category Prototype-Guided Vision-Language Framework for Long-Tail Recognition0
Parameter-Efficient Transfer Learning for Remote Sensing Image-Text RetrievalCode1
EVE: Efficient Vision-Language Pre-training with Masked Prediction and Modality-Aware MoE0
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