论文标题
在手写文档收藏上回答的无识别问题
Recognition-free Question Answering on Handwritten Document Collections
论文作者
论文摘要
近年来，在文档图像的问题回答（QA）的研究领域取得了长足的进步。文档图像分析社区的当前质量检查方法主要集中在机器打印的文档上，并且在手写上的表现相当有限。这主要是由于手写文档上的识别性能降低。为了解决这个问题，我们提出了一种无识别的质量质量检查方法，尤其是为手写文档图像收集而设计的。我们提出了一种强大的文档检索方法以及两个QA模型。我们的方法在具有挑战性的Benthamqa和HW-Squad数据集上优于最新的无识别模型。
In recent years, considerable progress has been made in the research area of Question Answering (QA) on document images. Current QA approaches from the Document Image Analysis community are mainly focusing on machine-printed documents and perform rather limited on handwriting. This is mainly due to the reduced recognition performance on handwritten documents. To tackle this problem, we propose a recognition-free QA approach, especially designed for handwritten document image collections. We present a robust document retrieval method, as well as two QA models. Our approaches outperform the state-of-the-art recognition-free models on the challenging BenthamQA and HW-SQuAD datasets.
