論文閱讀TextField: Learning A Deep Direction Field for Irregular Scene Text Detection
論文名稱： Learning A Deep Direction Field for Irregular Scene Text Detection 論文原文：原文鏈接 已有方法回顧 場景文本檢測大致分爲兩類：基於迴歸的方法和基於分割的方法。 基於迴歸的方法：通過直接回歸包含文本的水平/定向矩形或四邊形來調整一般物體檢測框架以檢測文本。缺點：用於檢測不規則形狀的文本時，性能顯着下降，例如彎曲文本。 基
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相關文章
- 1. 論文閱讀SLPR-Sliding Line Point Regression for Shape Robust Scene Text Detection
- 2. Rotation-sensitive regression for oriented scene text detection 論文閱讀
- 3. 【論文閱讀】Deep Residual Learning for Image Recognition
- 4. ICCV2017《Deep Direct Regression for Multi-Oriented Scene Text Detection》閱讀筆記
- 5. 【論文閱讀】Arbitrary Shape Scene Text Detection with Adaptive Text Region Representation
- 6. CRAFT：Character region awareness for text detection 論文閱讀
- 7. 論文閱讀：Deep Neural Networks for Object Detection
- 8. 【論文閱讀】【綜述】Deep Learning for 3D Point Clouds: A Survey
- 9. 論文閱讀：《Wide & Deep Learning for Recommender Systems》
- 10. Deep Relational Reasoning Graph Network for Arbitrary Shape Text Detection論文閱讀