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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

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Showing 101–110 of 188 papers

TitleStatusHype
Compositional Image-Text Matching and Retrieval by Grounding EntitiesCode0
Dissecting Deep Metric Learning Losses for Image-Text RetrievalCode0
Vision Meets Definitions: Unsupervised Visual Word Sense Disambiguation Incorporating Gloss InformationCode0
Unified Multimodal Pre-training and Prompt-based Tuning for Vision-Language Understanding and Generation—0
MedUnifier: Unifying Vision-and-Language Pre-training on Medical Data with Vision Generation Task using Discrete Visual Representations—0
A Concept-Centric Approach to Multi-Modality Learning—0
Active Mining Sample Pair Semantics for Image-text Matching—0
AdsCVLR: Commercial Visual-Linguistic Representation Modeling in Sponsored Search—0
Advanced Multimodal Deep Learning Architecture for Image-Text Matching—0
A Novel Attention-based Aggregation Function to Combine Vision and Language—0
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