Scene text detection with improved receptive field and adaptive feature fusion

2021 ◽  
Author(s):  
Liangjun Wang ◽  
Weijie Gu ◽  
Yuhang Ji
Keyword(s):  
Receptive Field ◽  
Feature Fusion ◽  
Text Detection ◽  
Scene Text Detection ◽  
Scene Text

scholarly journals CSFF-Net: Scene Text Detection Based on Cross-Scale Feature Fusion

Information ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 524
Author(s):  
Yuan Li ◽  
Mayire Ibrayim ◽  
Askar Hamdulla
Keyword(s):  
Information Flow ◽  
Feature Fusion ◽  
Feature Learning ◽  
Text Detection ◽  
Cross Layer ◽  
Scale Feature ◽  
Scene Text Detection ◽  
Scene Text ◽  
Feature Pyramid ◽  
Feature Information

In the last years, methods for detecting text in real scenes have made significant progress with an increase in neural networks. However, due to the limitation of the receptive field of the central nervous system and the simple representation of text by using rectangular bounding boxes, the previous methods may be insufficient for working with more challenging instances of text. To solve this problem, this paper proposes a scene text detection network based on cross-scale feature fusion (CSFF-Net). The framework is based on the lightweight backbone network Resnet, and the feature learning is enhanced by embedding the depth weighted convolution module (DWCM) while retaining the original feature information extracted by CNN. At the same time, the 3D-Attention module is also introduced to merge the context information of adjacent areas, so as to refine the features in each spatial size. In addition, because the Feature Pyramid Network (FPN) cannot completely solve the interdependence problem by simple element-wise addition to process cross-layer information flow, this paper introduces a Cross-Level Feature Fusion Module (CLFFM) based on FPN, which is called Cross-Level Feature Pyramid Network (Cross-Level FPN). The proposed CLFFM can better handle cross-layer information flow and output detailed feature information, thus improving the accuracy of text region detection. Compared to the original network framework, the framework provides a more advanced performance in detecting text images of complex scenes, and extensive experiments on three challenging datasets validate the realizability of our approach.

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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