Notes on "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks"
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks by Ren et al (2016) Region proposal based approaches for object detection tends to have the state-of-the-art performances in many benchmark datasets. Faster R-CNN uses convolutional network to propose regions which result in sharing the computation. Therefore, the Faster R-CNN is faster than R-CNN and Fast R-CNN (this is not real time capable!). See the slides below which is taken from a course on convolutional neural network from coursera. Faster R-CNN uses two convolutional neural networks; one is for the region proposal while other is for detection. As shown below the classifier uses proposals meaning "Region Proposal Network" gives the classifier where to look. To generate region proposal network, a convolutional network over the feature maps is proposed in which the inputs are n by n spatial window of the input feature map (each slideing window is mapped to a lower dimensional featu