method: SAR2018-12-19

Authors: Hui Li, Peng Wang, Chunhua Shen, Guyu Zhang

Description: We propose an easy-to-implement strong baseline for irregular scene text recognition, using off- the-shelf neural network components and only word-level annotations. It is composed of a 31-layer ResNet, an LSTM- based encoder-decoder framework and a 2-dimensional attention module. Despite its simplicity, the proposed method is robust. It achieves state-of-the-art performance on irregular text recognition benchmarks and comparable results on regular text datasets.

method: SAR tf-reproduce2019-10-14

Ranking Table

Description Paper Source Code
DateMethodTotal Edit distance (case sensitive)Correctly Recognised Words (case sensitive)T.E.D. (case insensitive)C.R.W. (case insensitive)
2018-12-19SAR437.164267.40%203.144678.82%
2020-01-11SAR_tensorflow_reproduced1,031.105741.36%333.159269.19%
2019-10-14SAR tf-reproduce843.437440.73%494.621055.66%
2019-10-14transformer-based method807.539139.24%454.970854.45%

Ranking Graphic

Ranking Graphic