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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

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Showing 176–188 of 188 papers

TitleStatusHype
ImageBERT: Cross-modal Pre-training with Large-scale Weak-supervised Image-Text Data—0
Learning fragment self-attention embeddings for image-text matchingCode0
UNITER: Learning UNiversal Image-TExt Representations—0
Learning Visual Relation Priors for Image-Text Matching and Image Captioning with Neural Scene Graph Generators—0
Unicoder-VL: A Universal Encoder for Vision and Language by Cross-modal Pre-training—0
Matching Images and Text with Multi-modal Tensor Fusion and Re-rankingCode0
Knowledge Aware Semantic Concept Expansion for Image-Text Matching—0
Position Focused Attention Network for Image-Text MatchingCode0
ParNet: Position-aware Aggregated Relation Network for Image-Text matching—0
Deep Cross-Modal Projection Learning for Image-Text MatchingCode0
Cross-modal Subspace Learning for Fine-grained Sketch-based Image Retrieval—0
Learning Two-Branch Neural Networks for Image-Text Matching TasksCode0
Dual Attention Networks for Multimodal Reasoning and MatchingCode0
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