# Deep Matching Prior Network: Toward Tighter Multi-oriented Text Detection

arXiv: https://arxiv.org/abs/1703.01425 · HTML: https://mlsanity.com/paper/1703.01425/

## Key facts

- Cited by 31 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Mar 2017.

## Built on by (most cited first, 30 of 31)

- [Real-Time Scene Text Detection with Differentiable Binarization and Adaptive Scale Fusion](https://mlsanity.com/paper/2202.10304/) (2022)
- [ABCNet v2: Adaptive Bezier-Curve Network for Real-time End-to-end Text Spotting](https://mlsanity.com/paper/2105.03620/) (2021)
- [SPTS v2: Single-Point Scene Text Spotting](https://mlsanity.com/paper/2301.01635/) (2023)
- [SPTS: Single-Point Text Spotting](https://mlsanity.com/paper/2112.07917/) (2021)
- [TPSNet: Reverse Thinking of Thin Plate Splines for Arbitrary Shape Scene Text Representation](https://mlsanity.com/paper/2110.12826/) (2021)
- [Mask is All You Need: Rethinking Mask R-CNN for Dense and Arbitrary-Shaped Scene Text Detection](https://mlsanity.com/paper/2109.03426/) (2021)
- [Industrial Scene Text Detection with Refined Feature-attentive Network](https://mlsanity.com/paper/2110.12663/) (2021)
- [Towards Robust Real-Time Scene Text Detection: From Semantic to Instance Representation Learning](https://mlsanity.com/paper/2308.07202/) (2023)
- [Turning a CLIP Model into a Scene Text Spotter](https://mlsanity.com/paper/2308.10408/) (2023)
- [Zoom Text Detector](https://mlsanity.com/paper/2209.03014/) (2022)
- [TRIE++: Towards End-to-End Information Extraction from Visually Rich Documents](https://mlsanity.com/paper/2207.06744/) (2022)
- [CBNet: A Plug-and-Play Network for Segmentation-Based Scene Text Detection](https://mlsanity.com/paper/2212.02340/) (2022)
- [Text-Aware Image Restoration with Diffusion Models](https://mlsanity.com/paper/2506.09993/) (2025)
- [Detection and Rectification of Arbitrary Shaped Scene Texts by using Text Keypoints and Links](https://mlsanity.com/paper/2103.00785/) (2021)
- [Plot2Spectra: an Automatic Spectra Extraction Tool](https://mlsanity.com/paper/2107.02827/) (2021)
- [A Survey on Deep Domain Adaptation and Tiny Object Detection Challenges, Techniques and Datasets](https://mlsanity.com/paper/2107.07927/) (2021)
- [Real-Time Text Detection with Similar Mask in Traffic, Industrial, and Natural Scenes](https://mlsanity.com/paper/2411.02794/) (2024)
- [Edge Approximation Text Detector](https://mlsanity.com/paper/2504.04001/) (2025)
- [HYCEDIS: HYbrid Confidence Engine for Deep Document Intelligence System](https://mlsanity.com/paper/2206.02628/) (2022)
- [Marginalized Generalized IoU (MGIoU): A Unified Objective Function for Optimizing Any Convex Parametric Shapes](https://mlsanity.com/paper/2504.16443/) (2025)
- [EK-Net:Real-time Scene Text Detection with Expand Kernel Distance](https://mlsanity.com/paper/2401.11704/) (2024)
- [Artistic-style text detector and a new Movie-Poster dataset](https://mlsanity.com/paper/2406.16307/) (2024)
- [Automated sign detection across the Electronic Babylonian Library: A large-scale dataset and end-to-end cuneiform OCR pipeline](https://mlsanity.com/paper/2606.22608/) (2026)
- [A DCNN-based Arbitrarily-Oriented Object Detector for Quality Control and Inspection Application](https://mlsanity.com/paper/2101.07383/) (2021)
- [Which to Match? Selecting Consistent GT-Proposal Assignment for Pedestrian Detection](https://mlsanity.com/paper/2103.10091/) (2021)
- [Scene Text recognition with Full Normalization](https://mlsanity.com/paper/2109.01034/) (2021)
- [Attention-based Feature Decomposition-Reconstruction Network for Scene Text Detection](https://mlsanity.com/paper/2111.14340/) (2021)
- [DPTNet: A Dual-Path Transformer Architecture for Scene Text Detection](https://mlsanity.com/paper/2208.09878/) (2022)
- [Box2Poly: Memory-Efficient Polygon Prediction of Arbitrarily Shaped and Rotated Text](https://mlsanity.com/paper/2309.11248/) (2023)
- [Text Region Multiple Information Perception Network for Scene Text Detection](https://mlsanity.com/paper/2401.10017/) (2024)

## Abstract (arXiv)

Detecting incidental scene text is a challenging task because of multi-orientation, perspective distortion, and variation of text size, color and scale. Retrospective research has only focused on using rectangular bounding box or horizontal sliding window to localize text, which may result in redundant background noise, unnecessary overlap or even information loss. To address these issues, we propose a new Convolutional Neural Networks (CNNs) based method, named Deep Matching Prior Network (DMPNet), to detect text with tighter quadrangle. First, we use quadrilateral sliding windows in several specific intermediate convolutional layers to roughly recall the text with higher overlapping area and then a shared Monte-Carlo method is proposed for fast and accurate computing of the polygonal areas. After that, we designed a sequential protocol for relative regression which can exactly predict text with compact quadrangle. Moreover, a auxiliary smooth Ln loss is also proposed for further regressing the position of text, which has better overall performance than L2 loss and smooth L1 loss in terms of robustness and stability. The effectiveness of our approach is evaluated on a public word-level, multi-oriented scene text database, ICDAR 2015 Robust Reading Competition Challenge 4 "Incidental scene text localization". The performance of our method is evaluated by using F-measure and found to be 70.64%, outperforming the existing state-of-the-art method with F-measure 63.76%.