  Scene text detection is a challenging problem in computer vision. In this
paper, we propose a novel text detection network based on prevalent object
detection frameworks. In order to obtain stronger semantic feature, we adopt
ResNet as feature extraction layers and exploit multi-level feature by
combining hierarchical convolutional networks. A vertical proposal mechanism is
utilized to avoid proposal classification, while regression layer remains
working to improve localization accuracy. Our approach evaluated on ICDAR2013
dataset achieves F-measure of 0.91, which outperforms previous state-of-the-art
results in scene text detection.
