.png){kind=icon}
返回
Deep Multi-Scale Context Aware Feature Aggregation for Curved Scene Text Detection
.png){kind=icon}
PRE
AI
DOI：10.1109/TMM.2019.2952978.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Scene text plays a significant role in image and video understanding, which has made great progress in recent years. Most existing models on text detection in the wild have the assumption that all the texts are surrounded by a rotated rectangle or quadrangle. While there also exist lots of curved texts in the wild, which would not be bounded by a regular bounding box. In this paper, we develop a novel architecture to localize the text regions, which can deal with curved-shape scene texts. Specifically, we first design a text-related feature enhancement module by incorporating the prior knowledge of the text shape to enhance the feature representations. After that, based on the enhanced features, we employ a region proposal network to generate the candidate boxes of scene texts. For each text candidate, a pyramid region-of-interest pooling attention module is utilized to extract the fixed-size features. Finally, we exploit the box-aware context-based text segmentation module and box refinement network to obtain the location of scene text. Experiments are conducted on four challenging benchmarks CTW1500, totalTEXT, ICDAR-2015 and MLT, and the experimental results have demonstrated the superiority of our model.
Keyword:
Curved text detection
text-related feature enhancement
pyramid pooling attention
box-aware segmentation
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
9.7
论文数:
4.6K
被引数:
2.4W
机构
引用论文
.png){kind=icon}
分享收藏
Exercise and Anxiety Reduction: Examination of Temperature as an Explanation for Affective Change
PREAI
分享收藏
查看更多内容