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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 171180 of 188 papers

TitleStatusHype
ImageBERT: Cross-modal Pre-training with Large-scale Weak-supervised Image-Text Data0
Learning fragment self-attention embeddings for image-text matchingCode0
UNITER: Learning UNiversal Image-TExt Representations0
UNITER: UNiversal Image-TExt Representation LearningCode1
Learning Visual Relation Priors for Image-Text Matching and Image Captioning with Neural Scene Graph Generators0
Visual Semantic Reasoning for Image-Text MatchingCode1
VL-BERT: Pre-training of Generic Visual-Linguistic RepresentationsCode1
Unicoder-VL: A Universal Encoder for Vision and Language by Cross-modal Pre-training0
Matching Images and Text with Multi-modal Tensor Fusion and Re-rankingCode0
Knowledge Aware Semantic Concept Expansion for Image-Text Matching0
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