method: I3CL2021-07-05
Authors: Jian Ye, Jing Zhang, Juhua Liu, Bo Du and Dacheng Tao
Affiliation: Wuhan University SigmaLab, JD Explore Academy
Email: leaf-yej@whu.edu.cn
Description: A arbitrary-shaped scene text detector based on Mask R-CNN. In this result, we use ResNeSt-101 as the backbone. Multi-scale training and testing are applied to get the final result. Our training datasets contain SynthText (pretrain), ArT, ICDAR2019-MLT, and part of LSVT.
method: DuXiaoman_OCR2020-05-21
Authors: Hang Yang, Yangchun Wan
Affiliation: Du Xiaoman Financial
Description: Our method is based on Mask RCNN. ResNeXt-152 as our backbone, we first pretrain the model on synthtext 800k, and then finetune on ArT2019,MLT2019 and part of LSVT. Multi-scale training and testing are used to get the final results.
AI-Lab, Du Xiaoman Financial
method: Tencent TEG OCR2019-12-17
Authors: Pei Xu, Hongzhen Wang, Shan Huang, Shen Huang, Qi Ju
Description: This method is based on Mask RCNN. We use resnet152 as backbone and don't use any ensemble methods. We train and test the model in multi scales. We synthesized curved data to pretrain the model. MLT2017 and a small part of LSVT data are used in training.
| Date | Method | Recall | Precision | Hmean | |||
|---|---|---|---|---|---|---|---|
| 2021-07-05 | I3CL | 81.03% | 87.26% | 84.03% | |||
| 2020-05-21 | DuXiaoman_OCR | 79.35% | 87.81% | 83.36% | |||
| 2019-12-17 | Tencent TEG OCR | 81.16% | 85.64% | 83.34% | |||
| 2019-11-04 | Sogou_OCR | 78.49% | 87.94% | 82.95% | |||
| 2019-04-30 | MEGVII_Detection | 76.68% | 89.64% | 82.65% | |||
| 2020-04-22 | Mask R-CNN | 78.55% | 86.43% | 82.30% | |||
| 2022-04-19 | TextBPN++(ResNet-50 with DCN) | 77.05% | 84.48% | 80.59% | |||
| 2019-05-01 | NJU-ImagineLab | 74.21% | 87.35% | 80.24% | |||
| 2019-04-29 | ArtDet-v2 | 73.54% | 86.45% | 79.48% | |||
| 2022-04-21 | I3CL(ViTAEv2-S) | 75.42% | 82.82% | 78.95% | |||
| 2019-04-26 | baseline_polygon | 75.38% | 82.51% | 78.79% | |||
| 2020-10-01 | TextFuseNet (ResNeXt-101) | 72.77% | 85.42% | 78.59% | |||
| 2019-04-30 | CUTeOCR | 71.56% | 86.57% | 78.36% | |||
| 2019-04-29 | Sg_ptd | 70.41% | 85.98% | 77.42% | |||
| 2019-04-28 | Alibaba-PAI | 73.25% | 79.18% | 76.10% | |||
| 2022-03-25 | TextBPN++(ResNet-50) | 71.07% | 81.14% | 75.77% | |||
| 2021-03-26 | TextFuseNet (ResNet-50) | 69.42% | 82.59% | 75.44% | |||
| 2019-04-30 | Fudan-Supremind Detection v3 | 71.61% | 79.26% | 75.24% | |||
| 2019-04-29 | SRCB_Art | 70.30% | 80.41% | 75.02% | |||
| 2019-04-30 | A scene text detection method based on maskrcnn | 66.25% | 85.69% | 74.72% | |||
| 2019-04-30 | DMText_art | 66.15% | 85.09% | 74.43% | |||
| 2021-04-28 | NN_Chinese_and_euro6 | 66.51% | 82.74% | 73.74% | |||
| 2019-04-30 | TEXT_SNIPER | 71.45% | 76.17% | 73.74% | |||
| 2019-04-28 | CLTDR | 65.92% | 82.58% | 73.32% | |||
| 2021-04-08 | AutoCV | 69.59% | 77.25% | 73.22% | |||
| 2019-04-29 | CRAFT | 68.93% | 77.25% | 72.85% | |||
| 2019-04-30 | MaskRCNN_Text | 67.28% | 79.06% | 72.69% | |||
| 2019-04-30 | QAQ | 63.45% | 83.76% | 72.21% | |||
| 2019-04-30 | MaskDet | 67.04% | 76.47% | 71.44% | |||
| 2019-04-24 | fdu_ai | 61.61% | 82.11% | 70.40% | |||
| 2019-04-30 | CCISTD | 60.72% | 81.16% | 69.47% | |||
| 2019-04-30 | Mask RCNN | 73.20% | 65.16% | 68.95% | |||
| 2019-05-01 | TextMask_V1 | 70.58% | 67.33% | 68.92% | |||
| 2019-04-22 | MFTD: Mask Filters for Text Detection | 63.05% | 72.09% | 67.27% | |||
| 2021-04-23 | HOCRA | 64.35% | 69.75% | 66.94% | |||
| 2019-04-25 | Art detect by vivo | 57.15% | 80.72% | 66.92% | |||
| 2019-04-29 | PAT-S.Y | 59.64% | 75.72% | 66.72% | |||
| 2019-04-16 | Art_test_baseline_task1 | 62.27% | 71.38% | 66.51% | |||
| 2019-04-30 | DMCA | 64.01% | 69.08% | 66.45% | |||
| 2019-04-30 | TMIS | 53.49% | 86.19% | 66.01% | |||
| 2021-04-28 | NN_euro6 | 51.76% | 85.50% | 64.48% | |||
| 2019-04-22 | mask rcnn | 55.61% | 74.83% | 63.81% | |||
| 2019-05-01 | Unicamp-SRBR-PN-1 | 57.59% | 68.02% | 62.37% | |||
| 2019-04-26 | TP | 51.62% | 78.18% | 62.18% | |||
| 2019-04-28 | Improved Progressive scale expansion Net | 52.24% | 75.88% | 61.88% | |||
| 2019-04-23 | 1 | 59.04% | 57.38% | 58.20% | |||
| 2019-04-27 | TextCohesion_1 | 43.66% | 68.08% | 53.20% | |||
| 2019-04-30 | EM-DATA | 45.11% | 61.34% | 51.99% | |||
| 2021-04-29 | HOCRA_base | 33.63% | 83.00% | 47.87% | |||
| 2019-04-26 | RAST: Robust Arbitrary Shape Text Detector | 35.44% | 71.08% | 47.30% | |||
| 2021-03-31 | inception baseline | 27.68% | 54.89% | 36.80% | |||
| 2019-04-30 | MSR | 0.46% | 0.55% | 0.50% |