  State-of-the-art scene text detection techniques predict quadrilateral boxes
that are prone to localization errors while dealing with straight or curved
text lines of different orientations and lengths in scenes. This paper presents
a novel multi-scale shape regression network (MSR) that is capable of locating
text lines of different lengths, shapes and curvatures in scenes. The proposed
MSR detects scene texts by predicting dense text boundary points that
inherently capture the location and shape of text lines accurately and are also
more tolerant to the variation of text line length as compared with the state
of the arts using proposals or segmentation. Additionally, the multi-scale
network extracts and fuses features at different scales which demonstrates
superb tolerance to the text scale variation. Extensive experiments over
several public datasets show that the proposed MSR obtains superior detection
performance for both curved and straight text lines of different lengths and
orientations.
