# Deep Residual Text Detection Network for Scene Text

arXiv: https://arxiv.org/abs/1711.04147 · HTML: https://mlsanity.com/paper/1711.04147/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Nov 2017.

## Built on by (most cited first, 2 of 2)

- [Context-Free TextSpotter for Real-Time and Mobile End-to-End Text Detection and Recognition](https://mlsanity.com/paper/2106.05611/) (2021)
- [Towards Detecting, Recognizing, and Parsing the Address Information from Bangla Signboard: A Deep Learning-based Approach](https://mlsanity.com/paper/2311.13222/) (2023)

## Abstract (arXiv)

Scene text detection is a challenging problem in computer vision. In this paper, we propose a novel text detection network based on prevalent object detection frameworks. In order to obtain stronger semantic feature, we adopt ResNet as feature extraction layers and exploit multi-level feature by combining hierarchical convolutional networks. A vertical proposal mechanism is utilized to avoid proposal classification, while regression layer remains working to improve localization accuracy. Our approach evaluated on ICDAR2013 dataset achieves F-measure of 0.91, which outperforms previous state-of-the-art results in scene text detection.