Learning Text Component Features via Convolutional Neural Networks for Scene Text Detection

2018 ◽  
Author(s):  
Wafa Khlif ◽  
Nibal Nayef ◽  
Jean-Christophe Burie ◽  
Jean-Marc Ogier ◽  
Adel Alimi
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Text Detection ◽  
Scene Text Detection ◽  
Scene Text ◽  
Text Component

scholarly journals Compact and Accurate Scene Text Detector

2020 ◽  
Vol 10 (6) ◽  
pp. 2096 ◽  
Author(s):  
Minjun Jeon ◽  
Young-Seob Jeong
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Convolutional Neural Networks ◽  
Text Detection ◽  
Floating Point ◽  
Learning Models ◽  
Proposed Model ◽  
Scene Text Detection ◽  
Scene Text

Scene text detection is the task of detecting word boxes in given images. The accuracy of text detection has been greatly elevated using deep learning models, especially convolutional neural networks. Previous studies commonly aimed at developing more accurate models, but their models became computationally heavy and worse in efficiency. In this paper, we propose a new efficient model for text detection. The proposed model, namely Compact and Accurate Scene Text detector (CAST), consists of MobileNetV2 as a backbone and balanced decoder. Unlike previous studies that used standard convolutional layers as a decoder, we carefully design a balanced decoder. Through experiments with three well-known datasets, we then demonstrated that the balanced decoder and the proposed CAST are efficient and effective. The CAST was about 1.1x worse in terms of the F1 score, but 30∼115x better in terms of floating-point operations per second (FLOPS).

Multi-oriented scene text detection by fixed-width multi-ratio rotation anchors

2021 ◽  
Vol 95 ◽  
pp. 107428
Author(s):  
Beiji Zou ◽  
Wenjun Yang ◽  
Shu Liu ◽  
Lingzi Jiang
Keyword(s):  
Text Detection ◽  
Scene Text Detection ◽  
Scene Text
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