  Recently, anchor-based methods have achieved great progress in face
detection. Once anchor design and anchor matching strategy determined, plenty
of positive anchors will be sampled. However, faces with extreme aspect ratio
always fail to be sampled according to standard anchor matching strategy. In
fact, the max IoUs between anchors and extreme aspect ratio faces are still
lower than fixed sampling threshold. In this paper, we firstly explore the
factors that affect the max IoU of each face in theory. Then, anchor matching
simulation is performed to evaluate the sampling range of face aspect ratio.
Besides, we propose a Wide Aspect Ratio Matching (WARM) strategy to collect
more representative positive anchors from ground-truth faces across a wide
range of aspect ratio. Finally, we present a novel feature enhancement module,
named Receptive Field Diversity (RFD) module, to provide diverse receptive
field corresponding to different aspect ratios. Extensive experiments show that
our method can help detectors better capture extreme aspect ratio faces and
achieve promising detection performance on challenging face detection
benchmarks, including WIDER FACE and FDDB datasets.
