Pyramidal feature representation is the common practice to address the challenge of scale
variation in object detection. However, the inconsistency across different feature scales is a
primary limitation for the single-shot detectors based on feature pyramid. In this work, we
propose a novel and data driven strategy for pyramidal feature fusion, referred to as
adaptively spatial feature fusion (ASFF). It learns the way to spatially filter conflictive
information to suppress the inconsistency, thus improving the scale-invariance of features …