# OCR-RTPS: An OCR-based real-time positioning system for the valet parking

arXiv: https://arxiv.org/abs/2212.04116 · HTML: https://mlsanity.com/paper/2212.04116/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 22 of its 80 references that are in the map.
- First posted on arXiv 8 Dec 2022.

## Builds on (most cited first, 22 of 22)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [EAST: An Efficient and Accurate Scene Text Detector](https://mlsanity.com/paper/1704.03155/) (2017)
- [COCO-Text: Dataset and Benchmark for Text Detection and Recognition in Natural Images](https://mlsanity.com/paper/1601.07140/) (2016)
- [Real-time Scene Text Detection with Differentiable Binarization](https://mlsanity.com/paper/1911.08947/) (2019)
- [Mask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary Shapes](https://mlsanity.com/paper/1908.08207/) (2019)
- [ABCNet: Real-time Scene Text Spotting with Adaptive Bezier-Curve Network](https://mlsanity.com/paper/2002.10200/) (2020)
- [Shape Robust Text Detection with Progressive Scale Expansion Network](https://mlsanity.com/paper/1903.12473/) (2019)
- [ICDAR2019 Robust Reading Challenge on Arbitrary-Shaped Text (RRC-ArT)](https://mlsanity.com/paper/1909.07145/) (2019)
- [ICDAR2019 Robust Reading Challenge on Multi-lingual Scene Text Detection and Recognition -- RRC-MLT-2019](https://mlsanity.com/paper/1907.00945/) (2019)
- [TextBoxes: A Fast Text Detector with a Single Deep Neural Network](https://mlsanity.com/paper/1611.06779/) (2016)
- [FOTS: Fast Oriented Text Spotting with a Unified Network](https://mlsanity.com/paper/1801.01671/) (2018)
- [Detecting Text in Natural Image with Connectionist Text Proposal Network](https://mlsanity.com/paper/1609.03605/) (2016)
- [Detecting Oriented Text in Natural Images by Linking Segments](https://mlsanity.com/paper/1703.06520/) (2017)
- [Fourier Contour Embedding for Arbitrary-Shaped Text Detection](https://mlsanity.com/paper/2104.10442/) (2021)
- [Look More Than Once: An Accurate Detector for Text of Arbitrary Shapes](https://mlsanity.com/paper/1904.06535/) (2019)
- [PAN++: Towards Efficient and Accurate End-to-End Spotting of Arbitrarily-Shaped Text](https://mlsanity.com/paper/2105.00405/) (2021)
- [Convolutional Character Networks](https://mlsanity.com/paper/1910.07954/) (2019)
- [Towards Unconstrained End-to-End Text Spotting](https://mlsanity.com/paper/1908.09231/) (2019)
- [Towards End-to-end Text Spotting with Convolutional Recurrent Neural Networks](https://mlsanity.com/paper/1707.03985/) (2017)
- [Towards End-to-End Text Spotting in Natural Scenes](https://mlsanity.com/paper/1906.06013/) (2019)
- [TextNet: Irregular Text Reading from Images with an End-to-End Trainable Network](https://mlsanity.com/paper/1812.09900/) (2018)
- [Exploiting User Mobility for WiFi RTT Positioning: A Geometric Approach](https://mlsanity.com/paper/2011.03698/) (2020)

## Built on by (most cited first, 4 of 4)

- [TextDiffuser: Diffusion Models as Text Painters](https://mlsanity.com/paper/2305.10855/) (2023)
- [TRINS: Towards Multimodal Language Models that Can Read](https://mlsanity.com/paper/2406.06730/) (2024)
- [A High-Quality Text-Rich Image Instruction Tuning Dataset via Hybrid Instruction Generation](https://mlsanity.com/paper/2412.16364/) (2024)
- [ARTIST: Improving the Generation of Text-rich Images with Disentangled Diffusion Models and Large Language Models](https://mlsanity.com/paper/2406.12044/) (2024)

## Abstract (arXiv)

Obtaining the position of ego-vehicle is a crucial prerequisite for automatic control and path planning in the field of autonomous driving. Most existing positioning systems rely on GPS, RTK, or wireless signals, which are arduous to provide effective localization under weak signal conditions. This paper proposes a real-time positioning system based on the detection of the parking numbers as they are unique positioning marks in the parking lot scene. It does not only can help with the positioning with open area, but also run independently under isolation environment. The result tested on both public datasets and self-collected dataset show that the system outperforms others in both performances and applies in practice. In addition, the code and dataset will release later.