Hand Detection Based on Multi-scale Fully Convolutional Networks

Accurate hand detection is a challenging task because of large variations of hand images in real-world scenarios. We present a simple yet powerful multi-scale fully convolutional network structure that yields fast and accurate hand detection on challenging VIVA dataset. The proposed model directly detects and locates hands in driver’s cab of various size, shape, appearance, and illumination in full images without time-consuming region proposal step. The simple model with the well-designed loss functions promotes the proposed approach to achieve very good hand detection results.