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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 171–180 of 188 papers

TitleStatusHype
UC2: Universal Cross-lingual Cross-modal Vision-and-Language Pre-training—0
UFO: A UniFied TransfOrmer for Vision-Language Representation Learning—0
Dynamic Visual Semantic Sub-Embeddings and Fast Re-Ranking—0
Uncertainty-based Cross-Modal Retrieval with Probabilistic Representations—0
Unicoder-VL: A Universal Encoder for Vision and Language by Cross-modal Pre-training—0
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
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