Interpretable 3D Human Action Analysis with Temporal Convolutional Networks
综述 3D人体动作识别的现代深度模型的鉴别力越来越强。随着最近3D人体骨骼动作再现技术的复兴，3D人体骨骼动作再现技术的质量和发展速度都有了长足的进步。然而，基于最先进的学习方法的内部工作原理在三维人体动作识别中仍然主要是黑盒子。在这项工作中，我们提出使用一种新的模型称为时间卷积神经网络(TCN)用于三维人体动作识别。与目前流行的基于lstm的递归神经网络模型相比，TCN为我们提供了一
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- 1. 论文：3D Convolutional Neural Networks for Human Action Recognition
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相关文章
- 1. 论文：3D Convolutional Neural Networks for Human Action Recognition
- 2. 3DCNN:3D Convolutional Neural Networks for Human Action Recognition
- 3. 3D Convolutional Neural Networks for Human Action Recognition
- 4. 译：3D Convolutional Neural Networks for Human Action Recognition
- 5. Graph Convolutional Networks for Temporal Action Localization
- 6. TCN: TEMPORAL CONVOLUTIONAL NETWORKS
- 7. 读书笔记9：Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition
- 8. 论文阅读笔记（三十九）：3D Convolutional Neural Networks for Human Action Recognition
- 9. Reading Note: Interpretable Convolutional Neural Networks
- 10. P-GCN：Graph Convolutional Networks for Temporal Action Localization 2019 ICCV