Scene Text Detection with Supervised Pyramid Context Network

Understand

Scene text detection methods based on deep learning have achieved remarkable results over the past years.

• However, due to the high diversity and complexity of natural scenes, previous state-of-the-art text detection methods may still produce a considerable amount of false positives, when applied to images captured in real-world environments.
• To tackle this issue, mainly inspired by Mask R-CNN, we propose in this paper an effective model for scene text detection, which is based on Feature Pyramid Network (FPN) and instance segmentation.
• We propose a supervised pyramid context network (SPCNET) to precisely locate text regions while suppressing false positives.