【视频行为识别】3D Convolutional Neural Networks for Human Action Recognition：
3D Convolutional Neural Networks for Human Action Recognition 一个卷积map的某一位置的值是通过卷积上一层的三个连续的帧的同一个位置的局部感受野得到的。 3D CNN架构包含一个硬连线hardwired层、3个卷积层、2个下采样层和一个全连接层。每个3D卷积核卷积的立方体是连续7帧，每帧patch大小是60x40； 1）应用了一个固定的
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- 1. 3D Convolutional Neural Networks for Human Action Recognition
- 2. 译：3D Convolutional Neural Networks for Human Action Recognition
- 3. 论文：3D Convolutional Neural Networks for Human Action Recognition
- 4. 3DCNN:3D Convolutional Neural Networks for Human Action Recognition
- 5. 【论文学习】3D Convolutional Neural Networks for Human Action Recognition
- 6. 论文笔记3D Convolutional Neural Networks for Human Action Recognition
- 7. 《3D Convolutional Neural Networks for Human Action Recognition》论文阅读笔记
- 8. 基于3D卷积神经网络的行为识别：3D Convolutional Neural Networks for Human Action Recognition
- 9. MiCT: Mixed 3D/2D convolutional tube for human action recognition
- 10. 译：Two-stream convolutional networks for action recognition in videos
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相关文章
- 1. 3D Convolutional Neural Networks for Human Action Recognition
- 2. 译：3D Convolutional Neural Networks for Human Action Recognition
- 3. 论文：3D Convolutional Neural Networks for Human Action Recognition
- 4. 3DCNN:3D Convolutional Neural Networks for Human Action Recognition
- 5. 【论文学习】3D Convolutional Neural Networks for Human Action Recognition
- 6. 论文笔记3D Convolutional Neural Networks for Human Action Recognition
- 7. 《3D Convolutional Neural Networks for Human Action Recognition》论文阅读笔记
- 8. 基于3D卷积神经网络的行为识别：3D Convolutional Neural Networks for Human Action Recognition
- 9. MiCT: Mixed 3D/2D convolutional tube for human action recognition
- 10. 译：Two-stream convolutional networks for action recognition in videos