Text Spotting
52 papers with code • 4 benchmarks • 6 datasets
Text Spotting is the combination of Scene Text Detection and Scene Text Recognition in an end-to-end manner. It is the ability to read natural text in the wild.
Libraries
Use these libraries to find Text Spotting models and implementationsDatasets
Most implemented papers
PGNet: Real-time Arbitrarily-Shaped Text Spotting with Point Gathering Network
With a PG-CTC decoder, we gather high-level character classification vectors from two-dimensional space and decode them into text symbols without NMS and RoI operations involved, which guarantees high efficiency.
Open Images V5 Text Annotation and Yet Another Mask Text Spotter
A large scale human-labeled dataset plays an important role in creating high quality deep learning models.
SwinTextSpotter: Scene Text Spotting via Better Synergy between Text Detection and Text Recognition
End-to-end scene text spotting has attracted great attention in recent years due to the success of excavating the intrinsic synergy of the scene text detection and recognition.
GLASS: Global to Local Attention for Scene-Text Spotting
In recent years, the dominant paradigm for text spotting is to combine the tasks of text detection and recognition into a single end-to-end framework.
Mask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary Shapes
Recently, models based on deep neural networks have dominated the fields of scene text detection and recognition.
Visual Semantic Re-ranker for Text Spotting
In this paper, we propose a post-processing approach to improve the accuracy of text spotting by using the semantic relation between the text and the scene.
You Only Recognize Once: Towards Fast Video Text Spotting
Video text spotting is still an important research topic due to its various real-applications.
Mask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary Shapes
Moreover, we further investigate the recognition module of our method separately, which significantly outperforms state-of-the-art methods on both regular and irregular text datasets for scene text recognition.
ICDAR2019 Robust Reading Challenge on Arbitrary-Shaped Text (RRC-ArT)
This paper reports the ICDAR2019 Robust Reading Challenge on Arbitrary-Shaped Text (RRC-ArT) that consists of three major challenges: i) scene text detection, ii) scene text recognition, and iii) scene text spotting.
Text Perceptron: Towards End-to-End Arbitrary-Shaped Text Spotting
Many approaches have recently been proposed to detect irregular scene text and achieved promising results.