Fused Text Segmentation Networks for Multi-oriented Scene Text Detection

In this paper, we introduce a novel end-end framework for multi-oriented scene text detection from an instanceaware segmentation perspective. We present Fused Text Segmentation Networks, which combine multi-level features during feature extracting as text instance may rely on finer feature expression compared to general objects. It detects and segments the text instance jointly and simultaneously, leveraging merits from both semantic segmentation task and region proposal based object detection task. Not involving any extra pipelines, our approach surpasses the current state of the art on multi-oriented scene text detection benchmarks: ICDAR2015 Incidental Scene Text and MSRA-TD500 reaching Hmean 84.1% and Hmean 82.0% respectively which suggests effectiveness of the proposed approach.