论文标题
漫画中无约束的文本检测
Unconstrained Text Detection in Manga
论文作者
论文摘要
对不受约束文本的检测和识别是研究中的一个空缺问题。漫画书中的文字具有不寻常的样式，可以引起文本检测的许多挑战。这项工作旨在以具有高度复杂的文本样式的漫画类型中的像素级别识别文本字符：日本漫画。为了克服缺乏具有单个角色级别注释的漫画数据集，我们创建了自己的。文本检测中的大多数文献都使用边界框指标，这不适合像素级评估。因此，我们实施了特殊指标来评估绩效。使用这些资源，我们设计和评估了一个深层网络模型，超过了大多数指标中漫画中文本检测的当前方法。
The detection and recognition of unconstrained text is an open problem in research. Text in comic books has unusual styles that raise many challenges for text detection. This work aims to identify text characters at a pixel level in a comic genre with highly sophisticated text styles: Japanese manga. To overcome the lack of a manga dataset with individual character level annotations, we create our own. Most of the literature in text detection use bounding box metrics, which are unsuitable for pixel-level evaluation. Thus, we implemented special metrics to evaluate performance. Using these resources, we designed and evaluated a deep network model, outperforming current methods for text detection in manga in most metrics.
