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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 7180 of 188 papers

TitleStatusHype
Towards Grounded Visual Spatial Reasoning in Multi-Modal Vision Language Models0
Your Negative May not Be True Negative: Boosting Image-Text Matching with False Negative EliminationCode1
Grounded Image Text Matching with Mismatched Relation Reasoning0
A Systematic Survey of Prompt Engineering on Vision-Language Foundation ModelsCode2
Advancing Visual Grounding with Scene Knowledge: Benchmark and MethodCode1
UniFine: A Unified and Fine-grained Approach for Zero-shot Vision-Language UnderstandingCode1
Towards Unified Text-based Person Retrieval: A Large-scale Multi-Attribute and Language Search BenchmarkCode1
Revisiting the Role of Language Priors in Vision-Language ModelsCode1
Improved Probabilistic Image-Text RepresentationsCode1
Are Diffusion Models Vision-And-Language Reasoners?Code1
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