# Detecting Multi-Oriented Text with Corner-based Region Proposals

arXiv: https://arxiv.org/abs/1804.02690 · HTML: https://mlsanity.com/paper/1804.02690/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Apr 2018.

## Built on by (most cited first, 3 of 3)

- [Detection of Furigana Text in Images](https://mlsanity.com/paper/2207.03960/) (2022)
- [DrawMon: A Distributed System for Detection of Atypical Sketch Content in Concurrent Pictionary Games](https://mlsanity.com/paper/2211.05429/) (2022)
- [Text-VQA Aug: Pipelined Harnessing of Large Multimodal Models for Automated Synthesis](https://mlsanity.com/paper/2511.02046/) (2025)

## Abstract (arXiv)

Previous approaches for scene text detection usually rely on manually defined sliding windows. This work presents an intuitive two-stage region-based method to detect multi-oriented text without any prior knowledge regarding the textual shape. In the first stage, we estimate the possible locations of text instances by detecting and linking corners instead of shifting a set of default anchors. The quadrilateral proposals are geometry adaptive, which allows our method to cope with various text aspect ratios and orientations. In the second stage, we design a new pooling layer named Dual-RoI Pooling which embeds data augmentation inside the region-wise subnetwork for more robust classification and regression over these proposals. Experimental results on public benchmarks confirm that the proposed method is capable of achieving comparable performance with state-of-the-art methods. The code is publicly available at https://github.com/xhzdeng/crpn