Graphonomy: Universal Human Parsing via Graph Transfer Learning
Graphonomy: Universal Human Parsing via Graph Transfer Learning(CVPR2019) 作者认为现在human parsing任务，都是每个网络针对每个不同的数据集调到最优而牺牲了泛化能力，所以想通过一个网络能统一处理各种human parsing的数据集，设计了一个通用的human parsing模型，可以通过统一来自不同领域或不同粒度
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相关文章
- 1. Graph Few-shot learning via Knowledge Transfer
- 2. Paper Note --- Transfer Learning via Dimensionality Reduction
- 3. human parsing—学习笔记
- 4. 论文阅读：Learning Human-Object Interactions by Graph Parsing Neural Networks
- 5. 《Universal Style Transfer via Feature Transforms》论文解读
- 6. 迁移学习论文阅读：Transfer Learning via Learning to Transfer
- 7. Transfer Learning for Item Recommendations and Knowledge Graph Completion
- 8. [paper] Multiple Human Parsing
- 9. transfer learning
- 10. (13)[ICLR16] Net2Net: ACCELERATING LEARNING VIA KNOWLEDGE TRANSFER