Hi there, apologies if this is a weird question, but I’m not very experienced and haven’t had much luck getting an answer.
I need to make a Faster-RCNN with a resnet101 backbone and no FPN (I plan to deal with scales otherwise) but I’m not entirely sure where I should be taking the feature maps from. I was thinking of using torchvision’s implementation of a Faster-RCNN.
I though of taking them from “conv4” or “conv5”, but I noticed examples that I believe used the result of the adaptive pooling. I imagined this would make it more flexible in terms of input image size, but I don’t know if it would be enough information for the RPN.
I’ve also seen examples written in other frameworks that seem to concatenate the outputs of conv4 and 5 somehow.
Thank you in advance