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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 5160 of 188 papers

TitleStatusHype
Are Diffusion Models Vision-And-Language Reasoners?Code1
A Deep Local and Global Scene-Graph Matching for Image-Text RetrievalCode1
IteRPrimE: Zero-shot Referring Image Segmentation with Iterative Grad-CAM Refinement and Primary Word EmphasisCode1
Improved Probabilistic Image-Text RepresentationsCode1
MMoE: Enhancing Multimodal Models with Mixtures of Multimodal Interaction ExpertsCode1
Learning with Noisy Correspondence for Cross-modal MatchingCode1
CLIP is Strong Enough to Fight Back: Test-time Counterattacks towards Zero-shot Adversarial Robustness of CLIPCode1
Learning Semantic Relationship Among Instances for Image-Text MatchingCode1
ECCV Caption: Correcting False Negatives by Collecting Machine-and-Human-verified Image-Caption Associations for MS-COCOCode1
Text-Guided Neural Image InpaintingCode1
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