End-to-End Learning of Deformable Mixture of Parts and Deep Convolutional Neural Networks for Human
1、文章整體類似[3][4]兩篇文章 2、作者指出在訓練的時候經常會出現沒有標註的人體部位預測了出來，這種情況對於錯誤反傳是有影響的，原因是因爲沒有考慮整體人體的關機位置關係 [4]這篇文章提出了用DCNN和deformable model結合在一起的方式進行訓練，能夠靈活的處理tree，star和loopy的結構 文章的主要貢獻三
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相關文章
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