論文閱讀：Neural Motifs: Scene Graph Parsing with Global Context
Neural-Motifs(CVPR2018) 文章鏈接 官方github Paper給motif的定義是：regularly appearing substructures in scene graph。 換句話說，subject和object的label對它們的relation影響很大，和DR-net差不多的想法，不過用了更復雜的網絡來實現。基於motif的想法，paper提出了一個新
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相關文章
- 1. 論文記錄：Neural Motifs: Scene Graph Parsing with Global Context (CVPR-18)
- 2. [GCPNet]Scene Parsing with Global Context Embedding
- 3. 論文閱讀理解 - Pyramid Scene Parsing Network
- 4. PSPNet：Pyramid Scene Parsing Network論文閱讀
- 5. 論文導讀｜Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing
- 6. 論文閱讀：《Human Parsing with Contextualized Convolutional Neural Network》ICCV 2015
- 7. 論文閱讀：Learning Human-Object Interactions by Graph Parsing Neural Networks
- 8. 論文閱讀SPCNet-Scene Text Detection with Supervised Pyramid Context Network
- 9. Graph-based Dependency Parsing with Graph Neural Networks
- 10. ACNet_ Adaptive Context Network for Scene Parsing