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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 101110 of 188 papers

TitleStatusHype
Dual Embodied-Symbolic Concept Representations for Deep Learning0
Dynamic and Compressive Adaptation of Transformers From Images to Videos0
Embedding Arithmetic of Multimodal Queries for Image Retrieval0
EntityCLIP: Entity-Centric Image-Text Matching via Multimodal Attentive Contrastive Learning0
EVE: Efficient Vision-Language Pre-training with Masked Prediction and Modality-Aware MoE0
Expressing Objects just like Words: Recurrent Visual Embedding for Image-Text Matching0
FSMR: A Feature Swapping Multi-modal Reasoning Approach with Joint Textual and Visual Clues0
Grounded Image Text Matching with Mismatched Relation Reasoning0
Hashing based Efficient Inference for Image-Text Matching0
Hire: Hybrid-modal Interaction with Multiple Relational Enhancements for Image-Text Matching0
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