Single Shot Text Detector with Regional Attention
文献类型：会议论文
| 作者 | Pan He; Weilin Huang; Tong He; Qile Zhu; Yu Qiao; Xiaolin Li |
| 出版日期 | 2017 |
| 会议地点 | 意大利威尼斯 |
| 英文摘要 | We present a novel single-shot text detector that directly outputs word-level bounding boxes in a natural image. We propose an attention mechanism which roughly identifies text regions via an automatically learned attentional map. This substantially suppresses background interference in the convolutional features, which is the key to producing accurate inference of words, particularly at extremely small sizes. This results in a single model that essentially works in a coarse-to-fine manner. It departs from recent FCN- based text detectors which cascade multiple FCN models to achieve an accurate prediction. Furthermore, we de- velop a hierarchical inception module which efficiently ag- gregates multi-scale inception features. This enhances local details, and also encodes strong context information, allow- ing the detector to work reliably on multi-scale and multi- orientation text with single-scale images. Our text detector achieves an F-measure of 77% on the ICDAR 2015 bench- mark, advancing the state-of-the-art results in [18, 28]. Demo is available at: http://sstd.whuang.org/ |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/11760]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 作者单位 | 2017 |
| 推荐引用方式 GB/T 7714 | Pan He,Weilin Huang,Tong He,et al. Single Shot Text Detector with Regional Attention[C]. 见:. 意大利威尼斯. |
入库方式： OAI收割
来源：深圳先进技术研究院
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