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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 8190 of 188 papers

TitleStatusHype
DT2I: Dense Text-to-Image Generation from Region Descriptions0
CLIP-Powered TASS: Target-Aware Single-Stream Network for Audio-Visual Question Answering0
A Novel Attention-based Aggregation Function to Combine Vision and Language0
More Than Just Attention: Improving Cross-Modal Attentions with Contrastive Constraints for Image-Text Matching0
Bridging the Modality Gap: Dimension Information Alignment and Sparse Spatial Constraint for Image-Text Matching0
Don't Stop Learning: Towards Continual Learning for the CLIP Model0
A Concept-Centric Approach to Multi-Modality Learning0
Breaking Through the Noisy Correspondence: A Robust Model for Image-Text Matching0
Multimodal Matching-aware Co-attention Networks with Mutual Knowledge Distillation for Fake News Detection0
Discrete-continuous Action Space Policy Gradient-based Attention for Image-Text Matching0
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