論文翻譯：Two-Stream 3D Convolutional Neural Network for Human Skeleton-Based Action Recognition
摘要:在三維人體動作識別中，如何有效地從骨骼序列中提取時空信息仍然是一個挑戰。雖然最近的動作識別方法是基於遞歸神經網絡的，表現出了突出的性能，但這些方法的缺點之一是傾向於過分強調時間信息。由於三維卷積神經網絡(3D CNN)是一種通過獲取三維信號之間的相關性，同時從空間和時間維度學習特徵的強大工具，本文提出了據我們所知，這是3D CNN在基於骨架的動作識別中的第一次應用。我們的方法包
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相關文章
- 1. 論文：3D Convolutional Neural Networks for Human Action Recognition
- 2. 譯：3D Convolutional Neural Networks for Human Action Recognition
- 3. 3D Convolutional Neural Networks for Human Action Recognition
- 4. 3DCNN:3D Convolutional Neural Networks for Human Action Recognition
- 5. 【論文學習】3D Convolutional Neural Networks for Human Action Recognition
- 6. 論文筆記3D Convolutional Neural Networks for Human Action Recognition
- 7. 《3D Convolutional Neural Networks for Human Action Recognition》論文閱讀筆記
- 8. MiCT: Mixed 3D/2D convolutional tube for human action recognition
- 9. 【論文翻譯】An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition
- 10. Human Action Recognition Using a Modified Convolutional Neural Network(經典文獻閱讀)