method: PMTD2019-04-30
Authors: Jingchao Liu, Xuebo Liu, Ding Liang
Description: Pyramid Mask Text Detector, see https://arxiv.org/abs/1903.11800 for detail.
method: SRCB_LSVT2019-04-29
Authors: Yi Yu, Haiyang Guo, Xiaobing Wang, Yingying Jiang
Description: We use Mask R-CNN for text detection in our submission, which extends Faster R-CNN by adding a branch for predicting an object mask in parallel with the existing branch for bounding box recognition. Mask R-CNN is simple to train and adds only a small overhead to Faster R-CNN. And Mask R-CNN is the state-of-the-art object detection framework now. Therefore, it is used here for text detection task. We use the Mask R-CNN in https://github.com/facebookresearch/Detectron and the backbone network is ResNext 101. Meanwhile, the object is text here and the number of classification classes is 2. Besides, polygon based NMS is used for post-processing to remove overlapped text regions.
method: Fudan-Supremind Detection2019-04-30
Authors: Yaowu Wei, Shangchao Su, Tairu Qiu, Xunyan Wang, Shaokang Lin, Zili Yi, Lei Deng, Mulin Xu, Jianqi Ma, Bin Li, Xiangyang Xue
Description: We propose a text segmentation algorithm based on Cascaded Mask-RCNN with deformable convolution and DenseASPP. And furthermore, we do some changes.
Date | Method | Recall | Precision | Hmean | |||
---|---|---|---|---|---|---|---|
2019-04-30 | PMTD | 75.60% | 80.69% | 78.06% | |||
2019-04-29 | SRCB_LSVT | 72.39% | 83.10% | 77.38% | |||
2019-04-30 | Fudan-Supremind Detection | 73.90% | 77.63% | 75.72% | |||
2019-04-30 | DMText_lsvt | 70.92% | 79.11% | 74.79% | |||
2019-04-26 | baseline_polygon_0.7 | 70.99% | 78.75% | 74.66% | |||
2019-04-30 | TMIS | 68.67% | 74.37% | 71.40% | |||
2021-04-13 | mypannet | 59.34% | 67.66% | 63.23% | |||
2019-04-29 | test4 | 54.82% | 71.60% | 62.10% | |||
2019-04-26 | PSENet_v2 | 59.22% | 64.65% | 61.81% | |||
2020-11-23 | hrnet_w40_casecade | 56.84% | 57.33% | 57.08% | |||
2019-04-30 | CRAFT | 51.34% | 55.59% | 53.38% | |||
2022-03-03 | db | 45.19% | 59.56% | 51.39% |