论文阅读：Scene Graph Generation by Iterative Message Passing
Iterative Message Passing(CVPR2017) 文章 问题是最开始的graph怎么得到？代码里还是用的full-connected graph作为初始化。 本方法中，如果有C种关系，那么网络中是C+1个关系的概率，多的一个代表none-relation，物体类别也一样，多出来一类代表background。 代码里，先将所有可能的relation都列出来了（任意两
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相关文章
- 1. 论文阅读：Factorizable Net: An Efficient Subgraph-based Framework for Scene Graph Generation
- 2. 通过迭代消息传递生成场景图Scene Graph Generation by Iterative Message Passing（2017）
- 3. 论文阅读：Sequence Generation by Editing Prototype
- 4. 论文阅读总结(Message Passing Attention Networks for Documents Understanding)
- 5. Graph R-CNN for Scene Graph Generation
- 6. 论文阅读 Question Generation
- 7. 论文阅读：Neural Motifs: Scene Graph Parsing with Global Context
- 8. SayAsYouWish:Fine-grained Control of Image Caption Generation with Abstract Scene Graphs ---- 论文阅读笔记
- 9. 论文阅读：Learning Human-Object Interactions by Graph Parsing Neural Networks
- 10. 论文阅读：Talking Face Generation by Adversarially Disentangled Audio-Visual Representation