method: Shopee MMU OCR2022-10-31
Authors: Jianqiang Liu, Hanfei Xu, Bin Zheng, Eric W, Ronnie T, Alex X
Affiliation: Shopee MMU OCR
Description: Our method adopts a transformer-based context-aware framework. We utilize a hybrid architecture encoder and a context-aware autoregressive decoder to construct the recognition pipeline. Finally, a simple but effective multi-model fusion strategy is adopted.
method: CLOVA-AI v22019-02-18
Authors: Jeonghun Baek, Junyeop Lee, Sungrae Park, Moonbin Yim, Seonghyeon Kim, Hwalsuk Lee
Description: We used Thin-plate-spline (TPS) based Spatial transformer network (STN) which normalizes the input text images, ResNet based feature extractor, BiLSTM, and attention mechanism.
This model was developed based on the analysis of scene text recognition modules.
See our paper and source code.
method: VARCO_v22020-12-15
Authors: Jusung Lee, Jaemyung Lee, Younghyun Lee, Joonsoo Lee
Affiliation: VARCO
Description: This work was supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government(MSIT) (No.1711097855, Text Localization and Recognition for Efficient Digital Contents Analysis)
| Date | Method | Total Edit distance (case sensitive) | Correctly Recognised Words (case sensitive) | T.E.D. (case insensitive) | C.R.W. (case insensitive) | |||
|---|---|---|---|---|---|---|---|---|
| 2022-10-31 | Shopee MMU OCR | 15.9567 | 96.53% | 10.9539 | 97.17% | |||
| 2019-02-18 | CLOVA-AI v2 | 26.9515 | 95.98% | 23.4836 | 96.35% | |||
| 2020-12-15 | VARCO_v2 | 36.8797 | 94.61% | 26.2131 | 95.89% | |||
| 2018-11-12 | CLOVA-AI / PAPAGO | 37.7934 | 94.52% | 30.7018 | 95.34% | |||
| 2020-09-04 | Hancom Vision | 39.0466 | 93.52% | 33.6133 | 93.97% | |||
| 2018-09-12 | Clova AI / Lens | 39.1422 | 94.25% | 36.3422 | 94.61% | |||
| 2020-01-20 | VARCO | 39.8552 | 93.79% | 28.8885 | 95.07% | |||
| 2020-09-04 | Huawei_GDE_AI | 40.7449 | 90.32% | 32.5216 | 91.60% | |||
| 2017-08-14 | TencentAILab | 42.0003 | 95.07% | 39.3454 | 95.34% | |||
| 2017-07-28 | Tencent Youtu | 48.1239 | 92.42% | 40.3711 | 93.42% | |||
| 2021-05-14 | Baseline | 62.0971 | 88.49% | 29.6273 | 94.52% | |||
| 2017-02-24 | HIK_OCR | 64.9531 | 90.78% | 42.3134 | 93.33% | |||
| 2016-06-23 | Baidu IDL | 70.3918 | 88.31% | 57.5299 | 89.95% | |||
| 2020-09-30 | SRIB-STRIDE (Scene Text Recognition In Device) | 72.7929 | 86.67% | 62.6314 | 87.58% | |||
| 2016-01-25 | SRC-B-TextProcessingLab | 74.4549 | 87.40% | 63.1787 | 88.95% | |||
| 2019-09-05 | juxinli | 78.9369 | 88.58% | 49.8043 | 91.32% | |||
| 2015-12-29 | SRC-B-TextProcessingLab | 88.2727 | 84.66% | 78.2512 | 86.12% | |||
| 2017-05-31 | CVTE_OCR | 93.4391 | 80.55% | 81.8130 | 82.19% | |||
| 2015-11-09 | Megvii-Image++ | 115.9124 | 82.83% | 94.0676 | 86.03% | |||
| 2013-04-06 | PhotoOCR | 122.7483 | 82.83% | 109.9012 | 85.30% | |||
| 2018-06-04 | English Test | 136.7660 | 77.72% | 123.9121 | 79.18% | |||
| 2016-12-05 | SemaMediaData&HPI_Real-time-VideoOCR | 151.5163 | 82.37% | 123.2516 | 84.75% | |||
| 2016-11-29 | CNN-WRDF | 209.1936 | 72.66% | 193.4747 | 74.14% | |||
| 2017-04-11 | Dycn | 270.7607 | 66.21% | 234.4990 | 70.68% | |||
| 2013-04-08 | PicRead | 332.3699 | 57.99% | 290.8327 | 61.92% | |||
| 2013-04-05 | NESP | 355.2411 | 64.20% | 340.3159 | 64.84% | |||
| 2013-04-05 | PLT | 379.0842 | 62.37% | 362.2196 | 63.11% | |||
| 2013-04-05 | MAPS | 396.6110 | 62.74% | 380.8603 | 63.29% | |||
| 2013-04-09 | Feild's Method | 422.1187 | 47.95% | 390.6199 | 52.33% | |||
| 2013-04-06 | PIONEER | 479.8208 | 53.70% | 426.8353 | 55.71% | |||
| 2013-05-08 | Baseline | 538.9557 | 45.30% | 517.9223 | 46.58% | |||
| 2013-04-05 | TextSpotter | 606.2886 | 26.85% | 597.2748 | 28.13% |