method: SRFormer (ResNet50-#1seg)2023-08-09
Authors: Qingwen Bu
Affiliation: Shanghai Jiao Tong University
Description: We first pre-train our model on SynthText150k, MLT17, LSVT and ICDAR19-ArT for 300k iterations and then tune it on ArT for 50k iterations. No TTA or any ensemble method is employed.
method: TextFuseNet (ResNeXt-101)2020-10-01
Authors: Jian Ye, Zhe Chen, Juhua Liu, Bo Du
Affiliation: Wuhan University
Email: leaf-yej@whu.edu.cn
Description: This is a preliminary evaluation result of TextFuseNet with ResNeXt-101. Multi-scale training and single-scale testing are used to get the final results. Sigma Lab, Wuhan University.
method: CUTeOCR2019-04-30
Authors: Zhuotao Tian, Zhicheng Yang, Pengyuan Lyu, Ruiyu Li
Description: We use MASK R-CNN as our baseline. We are from CUHK, HIT and Tencent Youtu Lab.
Description Paper Source Code
Date | Method | Recall | Precision | Hmean | |||
---|---|---|---|---|---|---|---|
2023-08-09 | SRFormer (ResNet50-#1seg) | 73.51% | 86.08% | 79.30% | |||
2020-10-01 | TextFuseNet (ResNeXt-101) | 72.77% | 85.42% | 78.59% | |||
2019-04-30 | CUTeOCR | 71.56% | 86.57% | 78.36% | |||
2022-07-11 | DPText-DETR (ResNet-50) | 73.70% | 82.97% | 78.06% | |||
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% | |||
2019-04-30 | DMText_art | 66.15% | 85.09% | 74.43% | |||
2019-04-30 | TEXT_SNIPER | 71.45% | 76.17% | 73.74% | |||
2019-04-29 | CRAFT | 68.93% | 77.25% | 72.85% | |||
2019-04-30 | MaskDet | 67.04% | 76.47% | 71.44% | |||
2019-04-30 | CCISTD | 60.72% | 81.16% | 69.47% | |||
2019-04-25 | Art detect by vivo | 57.15% | 80.72% | 66.92% | |||
2019-04-30 | DMCA | 64.01% | 69.08% | 66.45% | |||
2019-04-30 | TMIS | 53.49% | 86.19% | 66.01% | |||
2019-04-28 | Improved Progressive scale expansion Net | 52.24% | 75.88% | 61.88% | |||
2019-04-27 | TextCohesion_1 | 43.66% | 68.08% | 53.20% | |||
2019-04-30 | MSR | 0.46% | 0.55% | 0.50% |