HiCoS-Net: hierarchical cross-modal graph learning with dynamic attention for hard negative-aware image-text matching

Fine-grained image-text matching, which is pivotal to multimodal intelligence, has advanced semantic correspondence inference through inter-modal region-word aggregation. Despite the efficacy of this approach, it remains limited by its inability to accommodate the semantic associations of hard negat...

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Vydané v:	Journal of King Saud University. Computer and information sciences Ročník 37; číslo 9; s. 281 - 30
Hlavní autori:	Feng, Dingcheng, Luo, Ning, Zhang, Shudong, Zhou, Lijuan, Wei, Bing
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Cham Springer International Publishing 01.11.2025 Springer Nature B.V Springer
Predmet:	Adaptation Associations Attention Computer Imaging Computer Science Database Management Dynamic graph attention mechanism Effectiveness Embedding Embedding similarity graph Hard negative samples HiCoS-Net Hierarchical inter-modal semantic network Knowledge Learning Machine Learning Matching Neural networks Original Paper Pattern Recognition and Graphics Semantics Software Engineering/Programming and Operating Systems Systems and Data Security Theory of Computation Vision Hierarchical inter-modal semantic network Hard negative samples HiCoS-Net Dynamic graph attention mechanism Embedding similarity graph
ISSN:	1319-1578, 2213-1248, 1319-1578
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