# Artistic-style text detector and a new Movie-Poster dataset

arXiv: https://arxiv.org/abs/2406.16307 · HTML: https://mlsanity.com/paper/2406.16307/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 38 of its 66 references that are in the map.
- First posted on arXiv 24 Jun 2024.

## Builds on (most cited first, 30 of 38)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Semi-Supervised Classification with Graph Convolutional Networks](https://mlsanity.com/paper/1609.02907/) (2016)
- [Mask R-CNN](https://mlsanity.com/paper/1703.06870/) (2017)
- [Fast R-CNN](https://mlsanity.com/paper/1504.08083/) (2015)
- [SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation](https://mlsanity.com/paper/1511.00561/) (2015)
- [CCNet: Criss-Cross Attention for Semantic Segmentation](https://mlsanity.com/paper/1811.11721/) (2018)
- [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)
- [Real-time Scene Text Detection with Differentiable Binarization](https://mlsanity.com/paper/1911.08947/) (2019)
- [Arbitrary-Oriented Scene Text Detection via Rotation Proposals](https://mlsanity.com/paper/1703.01086/) (2017)
- [ICDAR2019 Robust Reading Challenge on Arbitrary-Shaped Text (RRC-ArT)](https://mlsanity.com/paper/1909.07145/) (2019)
- [TextBoxes: A Fast Text Detector with a Single Deep Neural Network](https://mlsanity.com/paper/1611.06779/) (2016)
- [TextSnake: A Flexible Representation for Detecting Text of Arbitrary Shapes](https://mlsanity.com/paper/1807.01544/) (2018)
- [Real-Time Scene Text Detection with Differentiable Binarization and Adaptive Scale Fusion](https://mlsanity.com/paper/2202.10304/) (2022)
- [Detecting Text in Natural Image with Connectionist Text Proposal Network](https://mlsanity.com/paper/1609.03605/) (2016)
- [Detecting Curve Text in the Wild: New Dataset and New Solution](https://mlsanity.com/paper/1712.02170/) (2017)
- [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)
- [PixelLink: Detecting Scene Text via Instance Segmentation](https://mlsanity.com/paper/1801.01315/) (2018)
- [TextField: Learning A Deep Direction Field for Irregular Scene Text Detection](https://mlsanity.com/paper/1812.01393/) (2018)
- [Salient Objects in Clutter: Bringing Salient Object Detection to the Foreground](https://mlsanity.com/paper/1803.06091/) (2018)
- [Turning a CLIP Model into a Scene Text Detector](https://mlsanity.com/paper/2302.14338/) (2023)
- [Deep Direct Regression for Multi-Oriented Scene Text Detection](https://mlsanity.com/paper/1703.08289/) (2017)
- [TextRay: Contour-based Geometric Modeling for Arbitrary-shaped Scene Text Detection](https://mlsanity.com/paper/2008.04851/) (2020)
- [MSR: Multi-Scale Shape Regression for Scene Text Detection](https://mlsanity.com/paper/1901.02596/) (2019)
- [Scene Text Detection with Supervised Pyramid Context Network](https://mlsanity.com/paper/1811.08605/) (2018)
- [MOST: A Multi-Oriented Scene Text Detector with Localization Refinement](https://mlsanity.com/paper/2104.01070/) (2021)

## Built on by (most cited first, 1 of 1)

- [How far have we gone in Generative Image Restoration? A study on its capability, limitations and evaluation practices](https://mlsanity.com/paper/2603.05010/) (2026)

## Abstract (arXiv)

Although current text detection algorithms demonstrate effectiveness in general scenarios, their performance declines when confronted with artistic-style text featuring complex structures. This paper proposes a method that utilizes Criss-Cross Attention and residual dense block to address the incomplete and misdiagnosis of artistic-style text detection by current algorithms. Specifically, our method mainly consists of a feature extraction backbone, a feature enhancement network, a multi-scale feature fusion module, and a boundary discrimination module. The feature enhancement network significantly enhances the model's perceptual capabilities in complex environments by fusing horizontal and vertical contextual information, allowing it to capture detailed features overlooked in artistic-style text. We incorporate residual dense block into the Feature Pyramid Network to suppress the effect of background noise during feature fusion. Aiming to omit the complex post-processing, we explore a boundary discrimination module that guides the correct generation of boundary proposals. Furthermore, given that movie poster titles often use stylized art fonts, we collected a Movie-Poster dataset to address the scarcity of artistic-style text data. Extensive experiments demonstrate that our proposed method performs superiorly on the Movie-Poster dataset and produces excellent results on multiple benchmark datasets. The code and the Movie-Poster dataset will be available at: https://github.com/biedaxiaohua/Artistic-style-text-detection