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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 111120 of 188 papers

TitleStatusHype
MAP: Multimodal Uncertainty-Aware Vision-Language Pre-training ModelCode1
AdsCVLR: Commercial Visual-Linguistic Representation Modeling in Sponsored Search0
GRIT-VLP: Grouped Mini-batch Sampling for Efficient Vision and Language Pre-trainingCode1
ALADIN: Distilling Fine-grained Alignment Scores for Efficient Image-Text Matching and RetrievalCode0
Zero-Shot Video Captioning with Evolving Pseudo-TokensCode1
Don't Stop Learning: Towards Continual Learning for the CLIP Model0
Open-Vocabulary Multi-Label Classification via Multi-Modal Knowledge TransferCode1
GR-GAN: Gradual Refinement Text-to-image GenerationCode0
CCMB: A Large-scale Chinese Cross-modal BenchmarkCode1
Language Models Can See: Plugging Visual Controls in Text GenerationCode2
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