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Detection and recognition of scene texts of arbitrary shapes remain a grandchallenge due to the super-rich text shape variation in text line orientations,lengths, curvatures, etc. This paper presents a mask-guided multi-task networkthat detects and rectifies scene texts of arbitrary shapes reliably. Threetypes of keypoints are detected which specify the centre line and so the shapeof text instances accurately. In addition, four types of keypoint links aredetected of which the horizontal links associate the detected keypoints of eachtext instance and the vertical links predict a pair of landmark points (foreach keypoint) along the upper and lower text boundary, respectively. Scenetexts can be located and rectified by linking up the associated landmark points(giving localization polygon boxes) and transforming the polygon boxes via thinplate spline, respectively. Extensive experiments over several public datasetsshow that the use of text keypoints is tolerant to the variation in textorientations, lengths, and curvatures, and it achieves superior scene textdetection and rectification performance as compared with state-of-the-artmethods.

Detection and Rectification of Arbitrary Shaped Scene Texts by using Text Keypoints and Links