In this paper, we propose a new approach of hierarchical convolutional neural network (CNN) for face detection. The first layer of our architecture is a binary classifier built on a deep convolutional neural network with spatial pyramid pooling (SPP). Spatial pyramid pooling reduces the computational complexity and remove the fixed-size constraint of the network. We only need to compute the feature maps from the entire image once and generate a fixed-length representation regardless of the image size and scale. To improve the localization effectiveness, in the second layer, we design a bounding box regression network to refine the relative high scored non-face output from the first layer. The proposed approach is evaluated on the AFW dataset, FDDB dataset and Pascal Faces, and it reaches the state-of-the-art performance. Also, we apply our bounding box regression network to refine the other detectors and find that it has effective generalization.
CITATION STYLE
Wu, L., Wang, Y., Long, J., & Liu., Z. (2015). Simple,Accurate and Robust Nonparametric Blind SR. Image and Graphics, 9217, 263–277. Retrieved from http://link.springer.com/10.1007/978-3-319-21978-3
Mendeley helps you to discover research relevant for your work.