PT Unknown
AU Raul Gomez
   Ali Furkan Biten
   Lluis Gomez
   Jaume Gibert
   Marçal Rusiñol
   Dimosthenis Karatzas
TI Selective Style Transfer for Text
BT 15th International Conference on Document Analysis and Recognition
PY 2019
BP 805
EP 812
DI 10.1109/ICDAR.2019.00134
DE transfer; text style transfer; data augmentation; scene text detection
AB This paper explores the possibilities of image style transfer applied to text maintaining the original transcriptions. Results on different text domains (scene text, machine printed text and handwritten text) and cross-modal results demonstrate that this is feasible, and open different research lines. Furthermore, two architectures for selective style transfer, which meanstransferring style to only desired image pixels, are proposed. Finally, scene text selective style transfer is evaluated as a data augmentation technique to expand scene text detection datasets, resulting in a boost of text detectors performance. Our implementation of the described models is publicly available.
ER