【论文笔记】CVPR2020 Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition
使用GCN进行skeleton-based action recognition Contribution 提出了两个设计： a disentangled multi-scale aggregation scheme a unified spatial-temporal graph convolutional module (G3D) 分别解决了两个问题： unbiased weight prob
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相关文章
- 1. Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition
- 2. 论文笔记--Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition
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- 7. 论文阅读《Long-term Temporal Convolutions for Action Recognition》
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- 9. 《Long-Term Temporal Convolutions for Action Recognition》 论文翻译
- 10. 论文阅读笔记 SPDA-CNN: Unifying Semantic Part Detection and Abstraction for Fine-grained Recognition