Overview

  • Number of checkpoints: 27

  • Number of configs: 24

  • Number of papers: 17

    • ALGORITHM: 15

    • BACKBONE: 1

    • PREPROCESSOR: 1

For supported datasets, see datasets overview.

Key Information Extraction Models

  • Number of checkpoints: 2

  • Number of configs: 2

  • Number of papers: 1

    • [ALGORITHM] Spatial Dual-Modality Graph Reasoning for Key Information Extraction ()

Named Entity Recognition Models

  • Number of checkpoints: 1

  • Number of configs: 1

  • Number of papers: 1

    • [ALGORITHM] Bert: Pre-Training of Deep Bidirectional Transformers for Language Understanding ()

Text Detection Models

  • Number of checkpoints: 14

  • Number of configs: 13

  • Number of papers: 7

    • [ALGORITHM] Deep Relational Reasoning Graph Network for Arbitrary Shape Text Detection ()

    • [ALGORITHM] Efficient and Accurate Arbitrary-Shaped Text Detection With Pixel Aggregation Network ()

    • [ALGORITHM] Fourier Contour Embedding for Arbitrary-Shaped Text Detection ()

    • [ALGORITHM] Mask R-CNN ()

    • [ALGORITHM] Real-Time Scene Text Detection With Differentiable Binarization ()

    • [ALGORITHM] Shape Robust Text Detection With Progressive Scale Expansion Network ()

    • [ALGORITHM] Textsnake: A Flexible Representation for Detecting Text of Arbitrary Shapes ()

Text Recognition Models

  • Number of checkpoints: 10

  • Number of configs: 8

  • Number of papers: 8

    • [ALGORITHM] An End-to-End Trainable Neural Network for Image-Based Sequence Recognition and Its Application to Scene Text Recognition ( )

    • [ALGORITHM] Nrtr: A No-Recurrence Sequence-to-Sequence Model for Scene Text Recognition ()

    • [ALGORITHM] On Recognizing Texts of Arbitrary Shapes With 2d Self-Attention ()

    • [ALGORITHM] Robustscanner: Dynamically Enhancing Positional Clues for Robust Text Recognition ()

    • [ALGORITHM] Segocr Simple Baseline. ()

    • [ALGORITHM] Show, Attend and Read: A Simple and Strong Baseline for Irregular Text Recognition ( )

    • [BACKBONE] Show, Attend and Read: A Simple and Strong Baseline for Irregular Text Recognition ( )

    • [PREPROCESSOR] Robust Scene Text Recognition With Automatic Rectification ()