- Task 1 - Text Localization
- Task 2 - Script identification
- Task 3 - Joint text detection and script identification
method: Baidu-VIS2019-05-08
Authors: Baidu-VIS
Description: We are from the Department of Computer Vision, Baidu Inc. Our approach follows the framework of LOMO and mainly upgrades the backbone network. For more details about LOMO, please refer to the paper: "Look More Than Once: An Accurate Detector for Text of Arbitrary Shapes", accepted by CVPR2019. (https://128.84.21.199/abs/1904.06535)
method: PMTD2019-03-23
Authors: Jingchao Liu, Xuebo Liu
Description: Pyramid Mask Text Detector, see https://arxiv.org/abs/1903.11800 for detail. Trained model and inference code will be released. If you have questions, please feel free to contact Jingchao Liu (liujingchao@sensetime.com) and Xuebo Liu (liuxuebo@sensetime.com)
method: 4Paradigm-Data-Intelligence2019-06-11
Authors: ACVG
Description: We are from the Group of Computer Vision, 4paradigm. Our approach mainly follows the framework of two-stage detection network. Use icdar2017mlt 9000 train images and icdar2019mlt 9000 train images.
| Date | Method | Hmean | Precision | Recall | Average Precision | |||
|---|---|---|---|---|---|---|---|---|
| 2019-05-08 | Baidu-VIS | 64.31% | 55.42% | 76.59% | 41.52% | |||
| 2019-03-23 | PMTD | 63.05% | 53.85% | 76.05% | 61.26% | |||
| 2019-06-11 | 4Paradigm-Data-Intelligence | 62.20% | 50.86% | 80.06% | 39.66% | |||
| 2019-06-02 | NJU-ImagineLab | 61.30% | 51.50% | 75.70% | 58.97% | |||
| 2019-05-23 | 4Paradigm-Data-Intelligence | 61.04% | 50.33% | 77.53% | 37.92% | |||
| 2019-03-19 | ccnet single scale | 57.62% | 49.65% | 68.63% | 47.01% | |||
| 2018-11-20 | Pixel-Anchor | 56.66% | 50.77% | 64.09% | 34.21% | |||
| 2019-03-29 | GNNets (single scale) | 56.54% | 49.30% | 66.29% | 44.67% | |||
| 2018-10-29 | Amap-CVLab | 56.25% | 47.01% | 70.00% | 49.59% | |||
| 2018-11-15 | USTC-NELSLIP | 55.58% | 43.95% | 75.59% | 60.29% | |||
| 2018-01-22 | FOTS_v2 | 55.33% | 47.58% | 66.08% | 46.29% | |||
| 2018-11-28 | CRAFT | 55.23% | 48.07% | 64.89% | 30.47% | |||
| 2018-05-18 | PSENet_NJU_ImagineLab (single-scale) | 54.57% | 45.44% | 68.28% | 30.21% | |||
| 2018-12-22 | PKU_VDIG | 53.84% | 41.91% | 75.29% | 54.46% | |||
| 2018-12-04 | Mask R-CNN -multi scale | 53.77% | 46.13% | 64.45% | 44.65% | |||
| 2019-07-15 | stela | 53.32% | 45.31% | 64.76% | 45.50% | |||
| 2018-03-12 | ATL Cangjie OCR | 53.18% | 42.20% | 71.88% | 56.17% | |||
| 2018-12-04 | SPCNet_TongJi & UESTC (multi scale) | 52.06% | 43.26% | 65.38% | 27.39% | |||
| 2017-06-28 | SCUT_DLVClab1 | 51.27% | 45.80% | 58.24% | 38.59% | |||
| 2017-11-09 | EAST++ | 51.07% | 43.27% | 62.30% | 29.75% | |||
| 2019-01-08 | ALGCD_CP | 50.60% | 41.17% | 65.65% | 27.30% | |||
| 2018-08-23 | Sogou_MM | 50.35% | 40.40% | 66.81% | 44.72% | |||
| 2018-12-02 | Shape-Aware Based Scene Text Detector (single scale) | 49.96% | 40.58% | 65.00% | 25.68% | |||
| 2019-05-30 | Thesis-SE | 45.58% | 37.34% | 58.49% | 23.54% | |||
| 2018-12-13 | AutoCV | 45.01% | 33.36% | 69.15% | 41.95% | |||
| 2018-12-03 | SPCNet_TongJi & UESTC (single scale) | 44.38% | 32.88% | 68.23% | 21.78% | |||
| 2018-12-05 | EPTN-SJTU | 43.88% | 36.03% | 56.10% | 21.90% | |||
| 2017-06-29 | SARI_FDU_RRPN_v1 | 39.40% | 32.19% | 50.76% | 24.45% | |||
| 2017-06-28 | SARI_FDU_RRPN_v0 | 38.55% | 28.94% | 57.72% | 30.92% | |||
| 2017-06-30 | TH-DL | 32.73% | 30.16% | 35.78% | 20.68% | |||
| 2019-01-03 | YY AI OCR Group | 31.43% | 25.24% | 41.65% | 13.07% | |||
| 2017-06-30 | Sensetime OCR | 27.39% | 17.11% | 68.68% | 44.78% | |||
| 2017-06-30 | linkage-ER-Flow | 14.40% | 10.71% | 21.99% | 4.02% |