论文翻译：Recognizing Human Actions as the Evolution of Pose Estimation Maps
大多数基于视频的动作识别方法选择从整个视频中提取特征来识别动作。杂乱的背景和非动作的运动限制了这些方法的性能，因为它们缺乏对人体运动的明确建模。根据人体姿态估计的最新进展，本文提出了一种新的识别人体动作的姿态估计地图的进化方法。我们观察到，姿态估计图作为姿态估计的副产品，保留了更丰富的人体线索，从而有利于动作识别，而不是依赖视频中不准确的人体姿态估计。具体来说，位姿估计图的演化可以分解为热图的演化
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相关文章
- 1. 【总结】Recognizing Human Actions as the Evolution of Pose Estimation Maps
- 2. 读书笔记23：Recognizing Human Actions as the Evolution of Pose Estimation Maps（CVPR2018）
- 3. 论文阅读: 3D Human Pose Estimation in the Wild by Adversarial Learning
- 4. Deep High-Resolution Representation Learning for Human Pose Estimation论文翻译阅读 - 2019CVPR
- 5. Deep High-Resolution Representation Learning for Human Pose Estimation论文翻译
- 6. 论文翻译：Stacked Hourglass Networks for Human Pose Estimation
- 7. DeepPose: Human Pose Estimation via Deep Neural Networks论文翻译
- 8. 3D Human Pose Estimation = 2D Pose Estimation + Matching(2017)
- 9. 论文翻译：FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
- 10. 【转】DensePose: Dense Human Pose Estimation In The Wild