A large-scale dataset for end-to-end table recognition in the wild

[1]  Robin Abraham,et al.  PubTables-1M: Towards comprehensive table extraction from unstructured documents , 2021, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[2]  Gui-Song Xia,et al.  Parsing Table Structures in the Wild , 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

[3]  Dacheng Tao,et al.  TGRNet: A Table Graph Reconstruction Network for Table Structure Recognition , 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

[4]  Mayank Singh,et al.  TabLeX: A Benchmark Dataset for Structure and Content Information Extraction from Scientific Tables , 2021, ICDAR.

[5]  Peng Gao,et al.  PingAn-VCGroup's Solution for ICDAR 2021 Competition on Scientific Literature Parsing Task B: Table Recognition to HTML , 2021, ArXiv.

[6]  C. V. Jawahar,et al.  CDeC-Net: Composite Deformable Cascade Network for Table Detection in Document Images , 2020, 2020 25th International Conference on Pattern Recognition (ICPR).

[7]  Ravishankar Chityala,et al.  Affine Transformation , 2020, Image Processing and Acquisition using Python.

[8]  Antonio J. Plaza,et al.  Image Segmentation Using Deep Learning: A Survey , 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Antonio Jimeno-Yepes,et al.  Image-based table recognition: data, model, and evaluation , 2019, ECCV.

[10]  Yu Fang,et al.  ICDAR 2019 Competition on Table Detection and Recognition (cTDaR) , 2019, 2019 International Conference on Document Analysis and Recognition (ICDAR).

[11]  David S. Rosenberg,et al.  Challenges in End-to-End Neural Scientific Table Recognition , 2019, 2019 International Conference on Document Analysis and Recognition (ICDAR).

[12]  W. Keller,et al.  Thin plate spline interpolation , 2019, Journal of Geodesy.

[13]  Antonio Jimeno-Yepes,et al.  PubLayNet: Largest Dataset Ever for Document Layout Analysis , 2019, 2019 International Conference on Document Analysis and Recognition (ICDAR).

[14]  Heyan Huang,et al.  Complicated Table Structure Recognition , 2019, ArXiv.

[15]  Zhoujun Li,et al.  TableBank: Table Benchmark for Image-based Table Detection and Recognition , 2019, LREC.

[16]  Matti Pietikäinen,et al.  Deep Learning for Generic Object Detection: A Survey , 2018, International Journal of Computer Vision.

[17]  Waleed Ammar,et al.  Extracting Scientific Figures with Distantly Supervised Neural Networks , 2018, JCDL.

[18]  Zhi Tang,et al.  ICDAR2017 Competition on Page Object Detection , 2017, 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR).

[19]  Tamir Hassan,et al.  ICDAR 2013 Table Competition , 2013, 2013 12th International Conference on Document Analysis and Recognition.

[20]  Thomas Kieninger,et al.  An open approach towards the benchmarking of table structure recognition systems , 2010, DAS '10.

[21]  Antonio Torralba,et al.  LabelMe: A Database and Web-Based Tool for Image Annotation , 2008, International Journal of Computer Vision.