A Single-Shot Arbitrarily-Shaped Text Detector based on Context Attended Multi-Task Learning

15 Aug 2019 • Pengfei Wang • Chengquan Zhang • Fei Qi • Zuming Huang • Mengyi En • Junyu Han • Jingtuo Liu • Errui Ding • Guangming Shi

Detecting scene text of arbitrary shapes has been a challenging task over the past years. In this paper, we propose a novel segmentation-based text detector, namely SAST, which employs a context attended multi-task learning framework based on a Fully Convolutional Network (FCN) to learn various geometric properties for the reconstruction of polygonal representation of text regions... (read more)

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