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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 3140 of 188 papers

TitleStatusHype
Cross-modal Active Complementary Learning with Self-refining CorrespondenceCode1
DenseCLIP: Language-Guided Dense Prediction with Context-Aware PromptingCode1
Consensus-Aware Visual-Semantic Embedding for Image-Text MatchingCode1
Declaration-based Prompt Tuning for Visual Question AnsweringCode1
Deep Boosting Learning: A Brand-new Cooperative Approach for Image-Text MatchingCode1
Composing Object Relations and Attributes for Image-Text MatchingCode1
ComCLIP: Training-Free Compositional Image and Text MatchingCode1
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial NetworksCode1
Advancing Visual Grounding with Scene Knowledge: Benchmark and MethodCode1
Are Diffusion Models Vision-And-Language Reasoners?Code1
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