SOTAVerified

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
Efficient Medical Vision-Language Alignment Through Adapting Masked Vision ModelsCode1
Consensus-Aware Visual-Semantic Embedding for Image-Text MatchingCode1
Declaration-based Prompt Tuning for Visual Question AnsweringCode1
Deep Multimodal Neural Architecture SearchCode1
Composing Object Relations and Attributes for Image-Text MatchingCode1
Cross-modal Active Complementary Learning with Self-refining CorrespondenceCode1
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
Show:102550
← PrevPage 4 of 19Next →

No leaderboard results yet.