PyramidBox+ High Performance Detector for Finding Tiny Face
With the rapid development of deep convolutional neural network, face detection has made great progress in recent years. WIDER FACE dataset, as a main benchmark, contributes greatly to this area. A large amount of methods have been put forward where PyramidBox designs an effective data augmentation strategy (Data anchor sampling) and context based module for face detector. In this report, we improve each part to further boost the performance, including Balanced data anchor sampling, Dual PyramidAnchors and Dense Context Module. Specifically, Balanced data anchor sampling obtains more uniform sampling of faces with different sizes. Dual PyramidAnchors facilitate feature learning by introducing progressive anchor loss. Dense Context Module with dense connection not only enlarges receptive filed, but also passes information efficiently. Integrating these techniques, PyramidBox+ is constructed and achieves state of the art performance in hard set.
ArXiv