In this diagram, we see the two convs. It is said that these convs are a part of the Fully Convolution Network (FCN). In their paper Mask R-CNN (He et al., 2018), they mentioned something about the backbone (ResNets/Feature Pyramid Network ) and the head architecture of the model. I am just wondering how are they related to FCN and the two convs in the diagram. This diagram is also the first figure in their paper, just in case you can't see it.
The backbone refers to the network which takes as input the image and extracts the feature map upon which the rest of the network is based (the output of the backbone is the first block in your figure). "head" refers to everything after the RoI pooling -- in other words what you've labeled as FCN.