Use fast R CNN and cascade structure for face detection
Face detection is challenging in real world due to various poses, occlusions, lighting conditions and so on. Recently, deep learning achieves excellent performance on this task. In this paper, we propose a novel deep cascade convolutional network that uses Fast Region based Convolutional Network (Fast R CNN) [3] at the end of the structure. Our method achieves outstanding performance on the FDDB [1] and AFW [2] datasets. Especially, it achieves a high recall of 91.87% on the challenging FDDB benchmark, outperforming the state of the art methods. We adopt a cascaded structure to quickly reject the background regions first. At the last stage, we choose Fast R CNN to deal with the challenging candidates and it performs well.
2016 Visual Communications and Image Processing (VCIP)