Object Detection With Deep Neural Networks

Recently I red a series of papers about object detection using deep neural networks. Here is summary of the reading.

R-CNN: Region-based Convolutional Networks for Accurate Object Detection and Segmentation
用传统方法提出region proposal，train一个classifier和一个location regressor。classifier为了提高精度先用softmax train，然后fc层提出来的feature用svm fit，regressor单独作为一个network

用到了selective search生成proposal，从一个over-segmentation开始repeatedly merge similar regions. 然后每个region用传统的descriptor提feature，用bag-of-words model+ svm分类

Fast R-CNN


Faster R-CNN
提出一个region proposal network (RPN) 共享feature extraction的networks，不增加计算开销的情况下把上一版最耗时的region proposal步骤变成自动从network生成。