  Chinese keyword spotting is a challenging task as there is no visual blank
for Chinese words. Different from English words which are split naturally by
visual blanks, Chinese words are generally split only by semantic information.
In this paper, we propose a new Chinese keyword spotter for natural images,
which is inspired by Mask R-CNN. We propose to predict the keyword masks guided
by text line detection. Firstly, proposals of text lines are generated by
Faster R-CNN;Then, text line masks and keyword masks are predicted by
segmentation in the proposals. In this way, the text lines and keywords are
predicted in parallel. We create two Chinese keyword datasets based on RCTW-17
and ICPR MTWI2018 to verify the effectiveness of our method.
