Segmentation-based methods are widely used for scene text detection due to their superiority in describing arbitrary-shaped instances. However, two major problems still exist: (1) current label generation techniques mostly empirical and lack theoretical support, discouraging elaborate design; (2) as a result, most rely heavily on kernel segmentation which is unstable requires deliberate tuning....

Abstract Recent learning-based approaches show promising performance improvement for the scene text removal task but usually leave several remnants of and provide visually unpleasant results. In this work, a novel end-to-end framework is proposed based on accurate stroke detection. Specifically, problem decoupled into detection removal; we design separate networks to solve these two subproblems...

At present, multi-oriented text detection methods based on deep neural network have achieved promising performances various benchmarks. Nevertheless, there are still some difficulties for arbitrary shape detection, especially a simple and proper representation of instances. In this paper, pixel-based detector is proposed to facilitate the prediction instances with shapes in manner. Firstly, all...