Hi,
I'm looking into the implementation of Faster R-CNN in Gluon-CV and noticed that the feature extraction is split in 2 parts, before and after feature pooling. The second feature extraction step (with top_feature net) of the pooled features is to my knowledge not described in the Faster R-CNN paper written by Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun. Can someone describe why this additional top_feature extractor is added, or give a paper reference describing this step? Is it to simplify training or does it contribute to better detections during inference? Best, Blake Below the link to the above mentioned implementation: https://github.com/dmlc/gluon-cv/blob/master/gluoncv/model_zoo/rcnn/faster_rcnn/faster_rcnn.py --- [Visit Topic](https://discuss.mxnet.io/t/top-features-network-in-gluon-cv-faster-r-cnn/6355/1) or reply to this email to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.mxnet.io/email/unsubscribe/1791b87b3fe9f0b7a09ee2f6053e12fc54c4a7e425b0ac30f43ee3dd9c8accd4).
