Overview

• Number of checkpoints: 20

• Number of configs: 16

• Number of papers: 12

  • ALGORITHM: 11

  • BACKBONE: 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 (⇨)

Text Detection Models

• Number of checkpoints: 11

• Number of configs: 10

• Number of papers: 5

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

  • [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: 7

• Number of configs: 4

• Number of papers: 6

  • [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] 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 (⇨ ⇨)