这一篇论文是关于视频的物体跟踪的论文,我在组会中汇报的论文。附录中PPT是我总结的的要点,我简单总结一下这篇论文中的亮点:
1、cnn+lstm
2、使用LSTM体现tracker的状态,捕捉运动特征
3、cnn提取形态特征
4、skip connection将底层,中层,最高层的特征都放到lstm中。

论文阅读-Re 3 : Real-Time Recurrent Regression Networks for Object Tracking
论文阅读-Re 3 : Real-Time Recurrent Regression Networks for Object Tracking
论文阅读-Re 3 : Real-Time Recurrent Regression Networks for Object Tracking
论文阅读-Re 3 : Real-Time Recurrent Regression Networks for Object Tracking
论文阅读-Re 3 : Real-Time Recurrent Regression Networks for Object Tracking
论文阅读-Re 3 : Real-Time Recurrent Regression Networks for Object Tracking
论文阅读-Re 3 : Real-Time Recurrent Regression Networks for Object Tracking
论文阅读-Re 3 : Real-Time Recurrent Regression Networks for Object Tracking
论文阅读-Re 3 : Real-Time Recurrent Regression Networks for Object Tracking
论文阅读-Re 3 : Real-Time Recurrent Regression Networks for Object Tracking
论文阅读-Re 3 : Real-Time Recurrent Regression Networks for Object Tracking
论文阅读-Re 3 : Real-Time Recurrent Regression Networks for Object Tracking

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