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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 5160 of 188 papers

TitleStatusHype
Backdoor Attack on Unpaired Medical Image-Text Foundation Models: A Pilot Study on MedCLIPCode0
Negative Pre-aware for Noisy Cross-modal MatchingCode1
OT-Attack: Enhancing Adversarial Transferability of Vision-Language Models via Optimal Transport Optimization0
CILF-CIAE: CLIP-driven Image-Language Fusion for Correcting Inverse Age Estimation0
Synthesize, Diagnose, and Optimize: Towards Fine-Grained Vision-Language UnderstandingCode1
Emergent Open-Vocabulary Semantic Segmentation from Off-the-shelf Vision-Language ModelsCode1
MMoE: Enhancing Multimodal Models with Mixtures of Multimodal Interaction ExpertsCode1
Active Mining Sample Pair Semantics for Image-text Matching0
A New Fine-grained Alignment Method for Image-text Matching0
Cross-modal Active Complementary Learning with Self-refining CorrespondenceCode1
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