PS: Deformable Part Models are Convolutional Neural Networks_CVPR2015
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Deformable Part Models are Convolutional Neural Networks
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Ross Girshick, Forrest Iandola, Trevor Darrell, Jitendra Malik
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015
这篇文章把DPM重新公式化成CNN。必要的改造还是需要的，主要包含这几个，贴原文吧，比较好懂一点：
object geometry layer that encodes the relative
offsets of DPM parts.(为了实现object geometry layer，要实现distance tranform layer, distance transform (DT) pooling, which generalizes the familiar max-pooling operation used in CNNs. 作者先介绍了DT pooling，放在卷基层的下一层，用于实现OG Layer)
we describe how to extend a single-component DPM-CNN to a multi-component DPM-CNN using maxout units.。
把DPM用CNN表达后，那么后面的事情就水到渠成了。
idea，很多传统方法都可以表达成神经网络，如果对寻找神经网络架构比较困难，可以从传统方法中找到一个对应的神经网络结构，然后将参数通过学习的方式得到。
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