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 110 of 188 papers

TitleStatusHype
BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and GenerationCode5
VinVL: Revisiting Visual Representations in Vision-Language ModelsCode2
Aligning Information Capacity Between Vision and Language via Dense-to-Sparse Feature Distillation for Image-Text MatchingCode2
FiLo++: Zero-/Few-Shot Anomaly Detection by Fused Fine-Grained Descriptions and Deformable LocalizationCode2
MouSi: Poly-Visual-Expert Vision-Language ModelsCode2
Oscar: Object-Semantics Aligned Pre-training for Vision-Language TasksCode2
Language Models Can See: Plugging Visual Controls in Text GenerationCode2
A Systematic Survey of Prompt Engineering on Vision-Language Foundation ModelsCode2
Cross-Modal Implicit Relation Reasoning and Aligning for Text-to-Image Person RetrievalCode2
A Differentiable Semantic Metric Approximation in Probabilistic Embedding for Cross-Modal RetrievalCode1
Show:102550
← PrevPage 1 of 19Next →

No leaderboard results yet.