  Detection and recognition of scene texts of arbitrary shapes remain a grand
challenge due to the super-rich text shape variation in text line orientations,
lengths, curvatures, etc. This paper presents a mask-guided multi-task network
that detects and rectifies scene texts of arbitrary shapes reliably. Three
types of keypoints are detected which specify the centre line and so the shape
of text instances accurately. In addition, four types of keypoint links are
detected of which the horizontal links associate the detected keypoints of each
text instance and the vertical links predict a pair of landmark points (for
each keypoint) along the upper and lower text boundary, respectively. Scene
texts can be located and rectified by linking up the associated landmark points
(giving localization polygon boxes) and transforming the polygon boxes via thin
plate spline, respectively. Extensive experiments over several public datasets
show that the use of text keypoints is tolerant to the variation in text
orientations, lengths, and curvatures, and it achieves superior scene text
detection and rectification performance as compared with state-of-the-art
methods.
