现代信息科技2026，Vol.10Issue(15)：34-38,42,6.DOI:10.19850/j.cnki.2096-4706.2026.15.007
融合双线性二部图注意力的场景图问答方法研究
Research on a Scene Graph Question Answering Method Integrating Bilinear Bipartite Graph Attention
加东东 1薛羽馨 1张兆馨 2李天宇2
作者信息
- 1. 延安大学 物理与电子信息学院,陕西 延安 716000||陕西省能源大数据智能处理省市共建重点实验室,陕西 延安 716000
- 2. 延安大学 物理与电子信息学院,陕西 延安 716000
- 折叠
摘要
Abstract
Scene graphs represent images as structured semantic graphs,where nodes denote objects and their attributes and edges denote relationships between objects,thereby enriching visual information representation.Research on scene graph generation shows remarkable progress,but question answering based on scene graphs still requires further exploration.To this end,this study constructs a Bilinear Bipartite Graph Attention Network(BB-GAN)framework that selects the most relevant nodes from the scene graph based on the question content.First,the question is encoded into a fully connected graph,and a graph attention network is used to iteratively update the information.Subsequently,a bipartite graph between the semantic structure graph and the scene graph is constructed,BB-GAN is used for node matching,and a modular attention mechanism is introduced to enhance modality alignment.Global scene features,keyword node features,and question features are adaptively fused for answer prediction.Experiments on the GQA dataset demonstrate that the proposed method significantly outperforms existing approaches on binary questions.Ablation studies further validate the effectiveness of BB-GAN.关键词
场景图问答/双线性二部图注意力网络/图注意力网络/模态对齐Key words
scene graph question answering/bilinear bipartite graph attention network/graph attention network/modality alignment分类
信息技术与安全科学引用本文复制引用
加东东,薛羽馨,张兆馨,李天宇..融合双线性二部图注意力的场景图问答方法研究[J].现代信息科技,2026,10(15):34-38,42,6.
