method: Tencent TEG OCR2020-03-15
Authors: Pei Xu, Shan Huang, Hongzhen Wang, Shen Huang, Qi Ju.
Description: We reimplemented the standalone recognition method according to the end-to-end text spotting code released by the Mask TextSpotter[TPAMI]. It is a seq-to-seq method based on 2D attention. We synthesize curved text images for pretraining by the method of VGG synthtext. We add public dataset including icdar2013-2015, CUTE, SVT, IIIT5k, RCTW2017, LSVT to finetune and don't use any private data.
method: Sogou_OCR2019-11-07
Authors: Jianzhong Xu, Liang Wu, Miao Wang, Hailong Wang,Lulu Xu, Long Ma, Xuefeng Su
Description: An arbitrary-shaped text detection method based Mask RCNN for detection and attention based method for recognition.
method: AntMaskText32023-05-06
Authors: JIe Wang, Tao Huang, Taoxu
Affiliation: Ant-Group
Description: Based on Maskrcnn + SPN + SAM, we select on MaskTextSpotterv3 as our baseline. we construct a dictionary with 5800 classes. Some public datasets are used in our experiments, including icdar2013, icdar2015, LSVT, RCTW, part of MLT, and ReCTS. In the 2D-attention module, we improve the representation ability to recognize the chinese characters.
Mask TextSpotter v3: Segmentation Proposal Network for Robust Scene Text Spotting
| Date | Method | Recall | Precision | Hmean | 1-NED | |||
|---|---|---|---|---|---|---|---|---|
| 2020-03-15 | Tencent TEG OCR | 66.61% | 70.30% | 68.40% | 67.12% | |||
| 2019-11-07 | Sogou_OCR | 58.33% | 65.68% | 61.78% | 62.49% | |||
| 2023-05-06 | AntMaskText3 | 50.73% | 66.23% | 57.46% | 56.50% | |||
| 2019-04-28 | baseline_0.5_class_5435 | 49.29% | 56.03% | 52.45% | 53.86% | |||
| 2019-04-28 | Alibaba-PAI | 50.55% | 66.17% | 57.32% | 53.36% | |||
| 2019-04-30 | QAQ3 | 39.44% | 53.96% | 45.57% | 46.01% | |||
| 2019-04-30 | Detection-Recognition | 40.77% | 60.29% | 48.64% | 45.84% | |||
| 2019-04-30 | So Cold 2.0 | 38.78% | 35.53% | 37.09% | 39.71% | |||
| 2019-04-29 | task3 | 30.03% | 49.84% | 37.48% | 34.03% | |||
| 2019-04-16 | Art-test_baseline_task3 | 26.43% | 33.07% | 29.38% | 31.89% | |||
| 2019-04-30 | CRAFT + TPS-ResNet v1 | 26.43% | 39.53% | 31.68% | 27.21% |