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Label distribution learning for scene text detection 被引量:1
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作者 Haoyu MA Ningning LU +3 位作者 junjun mei Tao GUAN Yu ZHANG Xin GENG 《Frontiers of Computer Science》 SCIE EI CSCD 2023年第6期5-12,共8页
Recently,segmentation-based scene text detection has drawn a wide research interest due to its flexibility in describing scene text instance of arbitrary shapes such as curved texts.However,existing methods usually ne... Recently,segmentation-based scene text detection has drawn a wide research interest due to its flexibility in describing scene text instance of arbitrary shapes such as curved texts.However,existing methods usually need complex post-processing stages to process ambiguous labels,i.e.,the labels of the pixels near the text boundary,which may belong to the text or background.In this paper,we present a framework for segmentation-based scene text detection by learning from ambiguous labels.We use the label distribution learning method to process the label ambiguity of text annotation,which achieves a good performance without using additional post-processing stage.Experiments on benchmark datasets demonstrate that our method produces better results than state-of-the-art methods for segmentation-based scene text detection. 展开更多
关键词 scene text detection multi-task learning label distribution learning
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