End-to-End Learning of Deformable Mixture of Parts and Deep Convolutional Neural Networks for Human
1、文章整体类似[3][4]两篇文章 2、作者指出在训练的时候经常会出现没有标注的人体部位预测了出来，这种情况对于错误反传是有影响的，原因是因为没有考虑整体人体的关机位置关系 [4]这篇文章提出了用DCNN和deformable model结合在一起的方式进行训练，能够灵活的处理tree，star和loopy的结构 文章的主要贡献三
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相关文章
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