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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
Learning Visual Relation Priors for Image-Text Matching and Image Captioning with Neural Scene Graph Generators—0
Uniformly Distributed Category Prototype-Guided Vision-Language Framework for Long-Tail Recognition—0
Uniform Masking Prevails in Vision-Language Pretraining—0
UNITER: Learning UNiversal Image-TExt Representations—0
Unpaired Referring Expression Grounding via Bidirectional Cross-Modal Matching—0
UPainting: Unified Text-to-Image Diffusion Generation with Cross-modal Guidance—0
ViLTA: Enhancing Vision-Language Pre-training through Textual Augmentation—0
ViUniT: Visual Unit Tests for More Robust Visual Programming—0
VL-Match: Enhancing Vision-Language Pretraining with Token-Level and Instance-Level Matching—0
VLM-HOI: Vision Language Models for Interpretable Human-Object Interaction Analysis—0
VL-NMS: Breaking Proposal Bottlenecks in Two-Stage Visual-Language Matching—0
Contrastive Cross-Modal Pre-Training: A General Strategy for Small Sample Medical Imaging—0
Weakly Supervised Referring Image Segmentation with Intra-Chunk and Inter-Chunk Consistency—0
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