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English(EN) ConRTF: Edge-Constrained Boundary Distribution Refinement for Realtime TransFormer Table Structure Recognition

新方法利用几何先验增强实时表格结构识别

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了ConRTF，一种用于改进文档图像中实时表格结构识别的新方法。该方法利用了边缘约束的细粒度定位损失（EFL），该损失编码了表格特有的几何先验，强调行的水平边界和列的垂直边界。ConRTF展示了数据效率，仅用2000-3000个带标注的表格即可实现稳健的准确性，并在基准数据集上显示出优于现有实时检测器的持续改进。 AI

影响 通过实现更准确的表格提取来改进文档理解流程，可能有利于数据分析和信息检索。

排序理由 该集群包含一篇详细介绍表格结构识别新方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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新方法利用几何先验增强实时表格结构识别

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该集群包含一篇详细介绍表格结构识别新方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Eliott Thomas, Tri-Cong Pham, Mickael Coustaty, Aurelie Joseph, Gaspar Deloin, Vincent Poulain d'Andecy, Jean-Marc Ogier, Antoine Doucet ·

    ConRTF：面向实时 Transformer 表格结构识别的边缘约束边界分布细化

    arXiv:2607.00734v1 Announce Type: cross Abstract: Table Structure Recognition (TSR) aims to recover the row and column layout of tables from document images, a key step in document understanding pipelines. Accurate TSR depends on precise boundary localization: small errors in row…

  2. arXiv cs.AI TIER_1 English(EN) · Antoine Doucet ·

    ConRTF：实时 Transformer 表格结构识别的边缘约束边界分布细化

    Table Structure Recognition (TSR) aims to recover the row and column layout of tables from document images, a key step in document understanding pipelines. Accurate TSR depends on precise boundary localization: small errors in row or column boundaries can propagate into incorrect…

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