# BiP-Net: Bidirectional Perspective Strategy based Arbitrary-Shaped Text Detection Network

arXiv: https://arxiv.org/abs/2104.04903 · HTML: https://mlsanity.com/paper/2104.04903/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 15 of its 27 references that are in the map.
- First posted on arXiv 11 Apr 2021.

## Builds on (most cited first, 15 of 15)

- [CornerNet: Detecting Objects as Paired Keypoints](https://mlsanity.com/paper/1808.01244/) (2018)
- [Synthetic Data for Text Localisation in Natural Images](https://mlsanity.com/paper/1604.06646/) (2016)
- [Character Region Awareness for Text Detection](https://mlsanity.com/paper/1904.01941/) (2019)
- [EAST: An Efficient and Accurate Scene Text Detector](https://mlsanity.com/paper/1704.03155/) (2017)
- [TextSnake: A Flexible Representation for Detecting Text of Arbitrary Shapes](https://mlsanity.com/paper/1807.01544/) (2018)
- [Efficient and Accurate Arbitrary-Shaped Text Detection with Pixel Aggregation Network](https://mlsanity.com/paper/1908.05900/) (2019)
- [Rotation-Sensitive Regression for Oriented Scene Text Detection](https://mlsanity.com/paper/1803.05265/) (2018)
- [Detecting Curve Text in the Wild: New Dataset and New Solution](https://mlsanity.com/paper/1712.02170/) (2017)
- [ContourNet: Taking a Further Step toward Accurate Arbitrary-shaped Scene Text Detection](https://mlsanity.com/paper/2004.04940/) (2020)
- [TextField: Learning A Deep Direction Field for Irregular Scene Text Detection](https://mlsanity.com/paper/1812.01393/) (2018)
- [TextRay: Contour-based Geometric Modeling for Arbitrary-shaped Scene Text Detection](https://mlsanity.com/paper/2008.04851/) (2020)
- [Weakly Supervised Adversarial Domain Adaptation for Semantic Segmentation in Urban Scenes](https://mlsanity.com/paper/1904.09092/) (2019)
- [VSSA-NET: Vertical Spatial Sequence Attention Network for Traffic Sign Detection](https://mlsanity.com/paper/1905.01583/) (2019)
- [All you need is a second look: Towards Tighter Arbitrary shape text detection](https://mlsanity.com/paper/2004.12436/) (2020)
- [Efficient Scene Text Detection with Textual Attention Tower](https://mlsanity.com/paper/2002.03741/) (2020)

## Built on by (most cited first, 5 of 5)

- [Effect of Selection Format on LLM Performance](https://mlsanity.com/paper/2503.06926/) (2025)
- [MMO-IG: Multi-Class and Multi-Scale Object Image Generation for Remote Sensing](https://mlsanity.com/paper/2412.13684/) (2024)
- [EK-Net:Real-time Scene Text Detection with Expand Kernel Distance](https://mlsanity.com/paper/2401.11704/) (2024)
- [Focus Entirety and Perceive Environment for Arbitrary-Shaped Text Detection](https://mlsanity.com/paper/2409.16827/) (2024)
- [Text-Pass Filter: An Efficient Scene Text Detector](https://mlsanity.com/paper/2601.18098/) (2026)

## Abstract (arXiv)

Detecting irregular-shaped text instances is the main challenge for text detection. Existing approaches can be roughly divided into top-down and bottom-up perspective methods. The former encodes text contours into unified units, which always fails to fit highly curved text contours. The latter represents text instances by a number of local units, where the complicated network and post-processing lead to slow detection speed. In this paper, to detect arbitrary-shaped text instances with high detection accuracy and speed simultaneously, we propose a Bidirectional Perspective strategy based Network (BiP-Net). Specifically, a new text representation strategy is proposed to represent text contours from a top-down perspective, which can fit highly curved text contours effectively. Moreover, a contour connecting (CC) algorithm is proposed to avoid the information loss of text contours by rebuilding interval contours from a bottom-up perspective. The experimental results on MSRA-TD500, CTW1500, and ICDAR2015 datasets demonstrate the superiority of BiP-Net against several state-of-the-art methods.