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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 131140 of 188 papers

TitleStatusHype
ParNet: Position-aware Aggregated Relation Network for Image-Text matching0
Selectively Hard Negative Mining for Alleviating Gradient Vanishing in Image-Text Matching0
Step-Wise Hierarchical Alignment Network for Image-Text Matching0
SyncMask: Synchronized Attentional Masking for Fashion-centric Vision-Language Pretraining0
TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP0
Towards Deconfounded Image-Text Matching with Causal Inference0
Towards Efficient Cross-Modal Visual Textual Retrieval using Transformer-Encoder Deep Features0
Towards Grounded Visual Spatial Reasoning in Multi-Modal Vision Language Models0
Two-stream Hierarchical Similarity Reasoning for Image-text Matching0
UC2: Universal Cross-lingual Cross-modal Vision-and-Language Pre-training0
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