Faster RCNN

Introduction:

The work aims to boost the speed and the performance of fast-rcnn. The bottleneck of fast-rcnn is object proposal. So the main method will focus on region proposal.

Method:

Region Proposal Network (RPN)

For RPN, the input is CNN conv feature map, and the output is rectangular object proposals along with object scores.

In fast-rcnn, selective search is used, and RPN will replace it in faster-rcnn.

Here is the illustration.

Result Compared with Fast-rcnn:

With fewer proposals, the mAP still beat fast-rcnn, and the execution time is also much less than fast-rcnn. So faster-rcnn performs better than fast-rcnn on both speed and accuracy.