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http://dx.doi.org/10.9708/jksci.2020.25.07.047

Multi-scale face detector using anchor free method  

Lee, Dong-Ryeol (School of Computer Science and Engineering, Kangwon National University)
Kim, Yoon (Dept. of Computer Science and Engineering, Kangwon National University)
Publication Information
Journal of the Korea Society of Computer and Information / v.25, no.7, 2020 , pp. 47-55 More about this Journal
Abstract
In this paper, we propose one stage multi-scale face detector based Fully Convolution Network using anchor free method. Recently almost all state-of-the-art face detectors which predict location of faces using anchor-based methods rely on pre-defined anchor boxes. However this face detectors need to hyper-parameters and additional computation in training. The key idea of the proposed method is to eliminate hyper-parameters and additional computation using anchor free method. To do this, we apply two ideas. First, by eliminating the pre-defined set of anchor boxes, we avoid the additional computation and hyper-parameters related to anchor boxes. Second, our detector predicts location of faces using multi-feature maps to reduce foreground/background imbalance issue. Through Quantitative evaluation, the performance of the proposed method is evaluated and analyzed. Experimental results on the FDDB dataset demonstrate the effective of our proposed method.
Keywords
Face detection; Anchor free method; Multi-scale detection; Deep learning; Feature pyramid learning;
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