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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 1120 of 188 papers

TitleStatusHype
A Deep Local and Global Scene-Graph Matching for Image-Text RetrievalCode1
Align before Fuse: Vision and Language Representation Learning with Momentum DistillationCode1
BiCro: Noisy Correspondence Rectification for Multi-modality Data via Bi-directional Cross-modal Similarity ConsistencyCode1
A Differentiable Semantic Metric Approximation in Probabilistic Embedding for Cross-Modal RetrievalCode1
Cross-modal Active Complementary Learning with Self-refining CorrespondenceCode1
Adaptive Offline Quintuplet Loss for Image-Text MatchingCode1
Advancing Visual Grounding with Scene Knowledge: Benchmark and MethodCode1
ColorSwap: A Color and Word Order Dataset for Multimodal EvaluationCode1
ComCLIP: Training-Free Compositional Image and Text MatchingCode1
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial NetworksCode1
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