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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