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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 4150 of 188 papers

TitleStatusHype
BrainCLIP: Bridging Brain and Visual-Linguistic Representation Via CLIP for Generic Natural Visual Stimulus DecodingCode1
Fine-Grained Image-Text Matching by Cross-Modal Hard Aligning NetworkCode1
Learning Semantic Relationship Among Instances for Image-Text MatchingCode1
A Differentiable Semantic Metric Approximation in Probabilistic Embedding for Cross-Modal RetrievalCode1
ComCLIP: Training-Free Compositional Image and Text MatchingCode1
Self-supervised vision-language pretraining for Medical visual question answeringCode1
MAP: Multimodal Uncertainty-Aware Vision-Language Pre-training ModelCode1
GRIT-VLP: Grouped Mini-batch Sampling for Efficient Vision and Language Pre-trainingCode1
Zero-Shot Video Captioning with Evolving Pseudo-TokensCode1
Open-Vocabulary Multi-Label Classification via Multi-Modal Knowledge TransferCode1
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