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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
LLMScore: Unveiling the Power of Large Language Models in Text-to-Image Synthesis EvaluationCode1
MALM: Mask Augmentation based Local Matching for Food-Recipe RetrievalCode0
Discffusion: Discriminative Diffusion Models as Few-shot Vision and Language LearnersCode1
Probing the Role of Positional Information in Vision-Language Models0
Scene Text Recognition with Image-Text Matching-guided Dictionary0
Structure-CLIP: Towards Scene Graph Knowledge to Enhance Multi-modal Structured RepresentationsCode1
Vision Meets Definitions: Unsupervised Visual Word Sense Disambiguation Incorporating Gloss InformationCode0
RoCOCO: Robustness Benchmark of MS-COCO to Stress-test Image-Text Matching ModelsCode0
Multi-Modal Representation Learning with Text-Driven Soft Masks0
Multimodal Image-Text Matching Improves Retrieval-based Chest X-Ray Report GenerationCode1
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