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Faster R-CNN is an object detection model that enhances Fast R-CNN by using a region proposal network (RPN) with the CNN model.

The RPN shares full-image convolutional functionality with the sensing network.

It is a fully convolutional network that simultaneously predicts object boundaries and objectivity scores at each position.

The RPN is trained end-to-end to generate high-quality region proposals, which are used by Fast R-CNN for detection.

The RPN and Fast R-CNN are merged into a single network by sharing their convolutional functionality where the RPN component tells the unified network where to look.

Overall, Faster R-CNN consists of two modules.

The first module is a fully convolutional deep network that proposes regions.

The second module is the Fast R-CNN detector which uses the proposed regions.