.png){kind=icon}
返回
Unattached irregular scene text rectification with refined objective
.png){kind=icon}
PRE
AI
DOI：10.1016/j.neucom.2021.08.047.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Recently, text recognition tasks have reached a high level with deep learning-based methods. The techniques are widely applied in different fields, and nowadays most researchers aim to build an effective approach to deal with irregular text in scene images. In this work, we propose a GAN-based framework to rectify scene text with rotation, curving, or other distortions. Unlike previous rectification modules that rely on the recognition networks, our model can be utilized either as an independent model or an extra component. Therefore, annotations of the text content are not required to train the model. And we utilize a refined training objective with the proposed sample loss, which is able to effectively control pixels in the output images that are supposed to be sampled from input ones. Experiments on public benchmarks demonstrate the effectiveness of our method. The code will be publicly available on github soon. (c) 2021 Elsevier B.V. All rights reserved.
Keyword:
Irregular text recognition
Image rectification
Coarse-to-fine
Refined objective
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:
6.5
论文数:
2.5W
被引数:
6.5W
机构
暂无机构信息
引用论文
MORAN: A Multi-Object Rectified Attention Network for scene text recognitionMORAN: 用于场景文本识别的多目标校正注意力网络.png)
PATTERN RECOGNITION
PATTERN RECOGNITIONIF7.6
PREAI
分享收藏Multi-oriented text detection and verification in video frames and scene imagesNEUROCOMPUTING
OAAI
NEUROCOMPUTINGIF6.5
OAAI分享收藏Date-field retrieval in scene image and video frames using text enhancement and shape codingNEUROCOMPUTINGOAAI
NEUROCOMPUTINGIF6.5
OAAI分享收藏
查看更多内容