  We study the problem of extracting text instance contour information from
images and use it to assist scene text detection. We propose a novel and
effective framework for this and experimentally demonstrate that: (1) A CNN
that can be effectively used to extract instance-level text contour from
natural images. (2) The extracted contour information can be used for better
scene text detection. We propose two ways for learning the contour task
together with the scene text detection: (1) as an auxiliary task and (2) as
multi-task cascade. Extensive experiments with different benchmark datasets
demonstrate that both designs improve the performance of a state-of-the-art
scene text detector and that a multi-task cascade design achieves the best
performance.
