In this paper, different from the single-dimensional correspondence with limited semantic expressive capability, we propose a novel enhanced semantic similarity learning (ESL), which generalizes both measure-units and their correspondences into a dynamic learnable framework to examine the multi-dimensional enhanced ...
Aug 22, 2023
Apr 5, 2024 · Abstract—Image-text matching is a fundamental task to bridge vision and language. The critical challenge lies in accurately learning the ...
Learning Semantic Relationship among Instances for Image-Text ...
github.com › CrossmodalGroup › HREM
In this paper, we argue that sample relations could help learn subtle differences for hard negative instances, and thus transfer shared knowledge for infrequent ...
PDF | Image-text matching is a fundamental task to bridge vision and language. The critical challenge lies in accurately learning the semantic.
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This paper proposes a novel hierarchical relation model- ing framework (HREM) for image-text matching. HREM not only captures fragment-level relations ...
A novel image-text representation learning network BAERL is proposed. ... It captures both inter- and intra-modality correlations between image regions and words.
The Paper List of Large Multi-Modality Model, Parameter-Efficient Finetuning, Vision-Language Pretraining, Conventional Image-Text Matching for Preliminary ...
Image-text matching is a fundamental task to bridge vision and language. The critical challenge lies in accurately learning the semantic similarity between ...
In this paper, we argue that sample relations could help learn subtle differences for hard negative instances, and thus transfer shared knowledge for infrequent ...
Missing: Enhanced | Show results with:Enhanced
Apr 28, 2024 · Abstract—Image-text matching remains a challenging task due to heterogeneous semantic diversity across modalities and insufficient distance ...