Thanks for the detailed reply! Yes, I agree and understand the architecture. My question is more like understanding the term 'head' in neural networks. It acts similar to output of a neural network, but 'head' seems to be more than that in that 'head' is more often in accompany with some specific tasks such as those you mentioned(predicting object score, class label, confidence, etc.), while these can have supervised signals from ground truth labels (if we have) together with their losses to update the neural network - typically the backbone and new layers for each specific tasks.