Object detection with R-CNN?

Question

What does R-CNN actually do? Is it like using features extracted by CNN to detect classes in a specified window area? Is there any tensorflow implementation for this?

Answer 1

R-CNN is using the following algorithm:

1. Get region proposals for object detection (using selective search).
2. For each region crop the area from the image and run it thorough a CNN which classify the object.

There are more advanced algorithms that are built upon this like fast-R-CNN and faster R-CNN.

fast-R-CNN:

1. Run the entire image through the CNN
2. For each region from the region proposals extract the area using "roi polling" layer and than classify the object.

faster R-CNN:

1. Run the entire image through the CNN
2. Using the features detected using the CNN find region proposals using a object proposals network.
3. For each object proposal extract the area using "roi polling" layer and than classify the object.

There are a lot of implantation in tensorflow specifically for faster R-CNN which is the most recent variant just google faster R-CNN tensorflow.

Good luck