Dually Supervised Feature Pyramid for Object Detection and Segmentation

Understand

Feature pyramid architecture has been broadly adopted in object detection and segmentation to deal with multi-scale problem.

• However, in this paper we show that the capacity of the architecture has not been fully explored due to the inadequate utilization of the supervision information.
• Such insufficient utilization is caused by the supervision signal degradation in back propagation.
• Thus inspired, we propose a dually supervised method, named dually supervised FPN (DSFPN), to enhance the supervision signal when training the feature pyramid network (FPN).