Neural Motifs: Scene Graph Parsing with Global Context

@article{Zellers2017NeuralMS,
  title={Neural Motifs: Scene Graph Parsing with Global Context},
  author={Rowan Zellers and Mark Yatskar and Sam Thomson and Yejin Choi},
  journal={CoRR},
  year={2017},
  volume={abs/1711.06640}
}
We investigate the problem of producing structured graph representations of visual scenes. Our work analyzes the role of motifs: regularly appearing substructures in scene graphs. We present new quantitative insights on such repeated structures in the Visual Genome dataset. Our analysis shows that object labels are highly predictive of relation labels but not vice-versa. We also find that there are recurring patterns even in larger subgraphs: more than 50% of graphs contain motifs involving at… CONTINUE READING