Real-Time Scene Text Detection With Differentiable Binarization and Adaptive Scale Fusion

Recently, segmentation-based scene text detection methods have drawn extensive attention in the scene text detection field, because of their superiority in detecting the text instances of arbitrary shapes and extreme aspect ratios, profiting from the pixel-level descriptions. However, the vast major...

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Vydané v:IEEE transactions on pattern analysis and machine intelligence Ročník 45; číslo 1; s. 919 - 931
Hlavní autori: Liao, Minghui, Zou, Zhisheng, Wan, Zhaoyi, Yao, Cong, Bai, Xiang
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States IEEE 01.01.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Accuracy
Algorithms
arbitrary shapes
Aspect ratio
Feature extraction
Feature maps
Fuses
Image segmentation
Inference algorithms
Modules
Optimization
Prediction algorithms
real-time
Robustness
Scene text detection
Segmentation
Shape
ISSN:0162-8828, 1939-3539, 2160-9292, 1939-3539
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Shrnutí:Recently, segmentation-based scene text detection methods have drawn extensive attention in the scene text detection field, because of their superiority in detecting the text instances of arbitrary shapes and extreme aspect ratios, profiting from the pixel-level descriptions. However, the vast majority of the existing segmentation-based approaches are limited to their complex post-processing algorithms and the scale robustness of their segmentation models, where the post-processing algorithms are not only isolated to the model optimization but also time-consuming and the scale robustness is usually strengthened by fusing multi-scale feature maps directly. In this paper, we propose a Differentiable Binarization (DB) module that integrates the binarization process, one of the most important steps in the post-processing procedure, into a segmentation network. Optimized along with the proposed DB module, the segmentation network can produce more accurate results, which enhances the accuracy of text detection with a simple pipeline. Furthermore, an efficient Adaptive Scale Fusion (ASF) module is proposed to improve the scale robustness by fusing features of different scales adaptively. By incorporating the proposed DB and ASF with the segmentation network, our proposed scene text detector consistently achieves state-of-the-art results, in terms of both detection accuracy and speed, on five standard benchmarks.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0162-8828
1939-3539
2160-9292
1939-3539
DOI:10.1109/TPAMI.2022.3155612