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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 111120 of 188 papers

TitleStatusHype
ImageBERT: Cross-modal Pre-training with Large-scale Weak-supervised Image-Text Data0
Image-Text Matching with Multi-View Attention0
Instruction-augmented Multimodal Alignment for Image-Text and Element Matching0
InterBERT: Vision-and-Language Interaction for Multi-modal Pretraining0
Is An Image Worth Five Sentences? A New Look into Semantics for Image-Text Matching0
Knowledge Aware Semantic Concept Expansion for Image-Text Matching0
Learning Comprehensive Representations with Richer Self for Text-to-Image Person Re-Identification0
Learning Textual Prompts for Open-World Semi-Supervised Learning0
Macroscopic Control of Text Generation for Image Captioning0
MASS: Overcoming Language Bias in Image-Text Matching0
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